yinchenghust commited on Oct 26, 2025

Commit

14c2cd5

verified ·

1 Parent(s): e47f86a

Upload folder using huggingface_hub

Browse files

Files changed (22) hide show

.gitattributes +1 -0
added_tokens.json +2155 -0
config.json +60 -0
generation_config.json +16 -0
image_processing_minicpmv.py +501 -0
merges.txt +0 -0
model-00001-of-00008.safetensors +3 -0
model-00002-of-00008.safetensors +3 -0
model-00003-of-00008.safetensors +3 -0
model-00004-of-00008.safetensors +3 -0
model-00005-of-00008.safetensors +3 -0
model-00006-of-00008.safetensors +3 -0
model-00007-of-00008.safetensors +3 -0
model-00008-of-00008.safetensors +3 -0
model.safetensors.index.json +856 -0
preprocessor_config.json +24 -0
processing_minicpmv.py +255 -0
special_tokens_map.json +112 -0
tokenization_minicpmv_fast.py +66 -0
tokenizer.json +3 -0
tokenizer_config.json +0 -0
vocab.json +0 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

added_tokens.json ADDED Viewed

	@@ -0,0 +1,2155 @@

+{
+  "</box>": 151674,
+  "</image>": 151670,
+  "</image_id>": 151682,
+  "</point>": 151678,
+  "</quad>": 151676,
+  "</ref>": 151672,
+  "</slice>": 151680,
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "</unit>": 151684,
+  "<action_0>": 151748,
+  "<action_1000>": 152748,
+  "<action_1001>": 152749,
+  "<action_1002>": 152750,
+  "<action_1003>": 152751,
+  "<action_1004>": 152752,
+  "<action_1005>": 152753,
+  "<action_1006>": 152754,
+  "<action_1007>": 152755,
+  "<action_1008>": 152756,
+  "<action_1009>": 152757,
+  "<action_100>": 151848,
+  "<action_1010>": 152758,
+  "<action_1011>": 152759,
+  "<action_1012>": 152760,
+  "<action_1013>": 152761,
+  "<action_1014>": 152762,
+  "<action_1015>": 152763,
+  "<action_1016>": 152764,
+  "<action_1017>": 152765,
+  "<action_1018>": 152766,
+  "<action_1019>": 152767,
+  "<action_101>": 151849,
+  "<action_1020>": 152768,
+  "<action_1021>": 152769,
+  "<action_1022>": 152770,
+  "<action_1023>": 152771,
+  "<action_1024>": 152772,
+  "<action_1025>": 152773,
+  "<action_1026>": 152774,
+  "<action_1027>": 152775,
+  "<action_1028>": 152776,
+  "<action_1029>": 152777,
+  "<action_102>": 151850,
+  "<action_1030>": 152778,
+  "<action_1031>": 152779,
+  "<action_1032>": 152780,
+  "<action_1033>": 152781,
+  "<action_1034>": 152782,
+  "<action_1035>": 152783,
+  "<action_1036>": 152784,
+  "<action_1037>": 152785,
+  "<action_1038>": 152786,
+  "<action_1039>": 152787,
+  "<action_103>": 151851,
+  "<action_1040>": 152788,
+  "<action_1041>": 152789,
+  "<action_1042>": 152790,
+  "<action_1043>": 152791,
+  "<action_1044>": 152792,
+  "<action_1045>": 152793,
+  "<action_1046>": 152794,
+  "<action_1047>": 152795,
+  "<action_1048>": 152796,
+  "<action_1049>": 152797,
+  "<action_104>": 151852,
+  "<action_1050>": 152798,
+  "<action_1051>": 152799,
+  "<action_1052>": 152800,
+  "<action_1053>": 152801,
+  "<action_1054>": 152802,
+  "<action_1055>": 152803,
+  "<action_1056>": 152804,
+  "<action_1057>": 152805,
+  "<action_1058>": 152806,
+  "<action_1059>": 152807,
+  "<action_105>": 151853,
+  "<action_1060>": 152808,
+  "<action_1061>": 152809,
+  "<action_1062>": 152810,
+  "<action_1063>": 152811,
+  "<action_1064>": 152812,
+  "<action_1065>": 152813,
+  "<action_1066>": 152814,
+  "<action_1067>": 152815,
+  "<action_1068>": 152816,
+  "<action_1069>": 152817,
+  "<action_106>": 151854,
+  "<action_1070>": 152818,
+  "<action_1071>": 152819,
+  "<action_1072>": 152820,
+  "<action_1073>": 152821,
+  "<action_1074>": 152822,
+  "<action_1075>": 152823,
+  "<action_1076>": 152824,
+  "<action_1077>": 152825,
+  "<action_1078>": 152826,
+  "<action_1079>": 152827,
+  "<action_107>": 151855,
+  "<action_1080>": 152828,
+  "<action_1081>": 152829,
+  "<action_1082>": 152830,
+  "<action_1083>": 152831,
+  "<action_1084>": 152832,
+  "<action_1085>": 152833,
+  "<action_1086>": 152834,
+  "<action_1087>": 152835,
+  "<action_1088>": 152836,
+  "<action_1089>": 152837,
+  "<action_108>": 151856,
+  "<action_1090>": 152838,
+  "<action_1091>": 152839,
+  "<action_1092>": 152840,
+  "<action_1093>": 152841,
+  "<action_1094>": 152842,
+  "<action_1095>": 152843,
+  "<action_1096>": 152844,
+  "<action_1097>": 152845,
+  "<action_1098>": 152846,
+  "<action_1099>": 152847,
+  "<action_109>": 151857,
+  "<action_10>": 151758,
+  "<action_1100>": 152848,
+  "<action_1101>": 152849,
+  "<action_1102>": 152850,
+  "<action_1103>": 152851,
+  "<action_1104>": 152852,
+  "<action_1105>": 152853,
+  "<action_1106>": 152854,
+  "<action_1107>": 152855,
+  "<action_1108>": 152856,
+  "<action_1109>": 152857,
+  "<action_110>": 151858,
+  "<action_1110>": 152858,
+  "<action_1111>": 152859,
+  "<action_1112>": 152860,
+  "<action_1113>": 152861,
+  "<action_1114>": 152862,
+  "<action_1115>": 152863,
+  "<action_1116>": 152864,
+  "<action_1117>": 152865,
+  "<action_1118>": 152866,
+  "<action_1119>": 152867,
+  "<action_111>": 151859,
+  "<action_1120>": 152868,
+  "<action_1121>": 152869,
+  "<action_1122>": 152870,
+  "<action_1123>": 152871,
+  "<action_1124>": 152872,
+  "<action_1125>": 152873,
+  "<action_1126>": 152874,
+  "<action_1127>": 152875,
+  "<action_1128>": 152876,
+  "<action_1129>": 152877,
+  "<action_112>": 151860,
+  "<action_1130>": 152878,
+  "<action_1131>": 152879,
+  "<action_1132>": 152880,
+  "<action_1133>": 152881,
+  "<action_1134>": 152882,
+  "<action_1135>": 152883,
+  "<action_1136>": 152884,
+  "<action_1137>": 152885,
+  "<action_1138>": 152886,
+  "<action_1139>": 152887,
+  "<action_113>": 151861,
+  "<action_1140>": 152888,
+  "<action_1141>": 152889,
+  "<action_1142>": 152890,
+  "<action_1143>": 152891,
+  "<action_1144>": 152892,
+  "<action_1145>": 152893,
+  "<action_1146>": 152894,
+  "<action_1147>": 152895,
+  "<action_1148>": 152896,
+  "<action_1149>": 152897,
+  "<action_114>": 151862,
+  "<action_1150>": 152898,
+  "<action_1151>": 152899,
+  "<action_1152>": 152900,
+  "<action_1153>": 152901,
+  "<action_1154>": 152902,
+  "<action_1155>": 152903,
+  "<action_1156>": 152904,
+  "<action_1157>": 152905,
+  "<action_1158>": 152906,
+  "<action_1159>": 152907,
+  "<action_115>": 151863,
+  "<action_1160>": 152908,
+  "<action_1161>": 152909,
+  "<action_1162>": 152910,
+  "<action_1163>": 152911,
+  "<action_1164>": 152912,
+  "<action_1165>": 152913,
+  "<action_1166>": 152914,
+  "<action_1167>": 152915,
+  "<action_1168>": 152916,
+  "<action_1169>": 152917,
+  "<action_116>": 151864,
+  "<action_1170>": 152918,
+  "<action_1171>": 152919,
+  "<action_1172>": 152920,
+  "<action_1173>": 152921,
+  "<action_1174>": 152922,
+  "<action_1175>": 152923,
+  "<action_1176>": 152924,
+  "<action_1177>": 152925,
+  "<action_1178>": 152926,
+  "<action_1179>": 152927,
+  "<action_117>": 151865,
+  "<action_1180>": 152928,
+  "<action_1181>": 152929,
+  "<action_1182>": 152930,
+  "<action_1183>": 152931,
+  "<action_1184>": 152932,
+  "<action_1185>": 152933,
+  "<action_1186>": 152934,
+  "<action_1187>": 152935,
+  "<action_1188>": 152936,
+  "<action_1189>": 152937,
+  "<action_118>": 151866,
+  "<action_1190>": 152938,
+  "<action_1191>": 152939,
+  "<action_1192>": 152940,
+  "<action_1193>": 152941,
+  "<action_1194>": 152942,
+  "<action_1195>": 152943,
+  "<action_1196>": 152944,
+  "<action_1197>": 152945,
+  "<action_1198>": 152946,
+  "<action_1199>": 152947,
+  "<action_119>": 151867,
+  "<action_11>": 151759,
+  "<action_1200>": 152948,
+  "<action_1201>": 152949,
+  "<action_1202>": 152950,
+  "<action_1203>": 152951,
+  "<action_1204>": 152952,
+  "<action_1205>": 152953,
+  "<action_1206>": 152954,
+  "<action_1207>": 152955,
+  "<action_1208>": 152956,
+  "<action_1209>": 152957,
+  "<action_120>": 151868,
+  "<action_1210>": 152958,
+  "<action_1211>": 152959,
+  "<action_1212>": 152960,
+  "<action_1213>": 152961,
+  "<action_1214>": 152962,
+  "<action_1215>": 152963,
+  "<action_1216>": 152964,
+  "<action_1217>": 152965,
+  "<action_1218>": 152966,
+  "<action_1219>": 152967,
+  "<action_121>": 151869,
+  "<action_1220>": 152968,
+  "<action_1221>": 152969,
+  "<action_1222>": 152970,
+  "<action_1223>": 152971,
+  "<action_1224>": 152972,
+  "<action_1225>": 152973,
+  "<action_1226>": 152974,
+  "<action_1227>": 152975,
+  "<action_1228>": 152976,
+  "<action_1229>": 152977,
+  "<action_122>": 151870,
+  "<action_1230>": 152978,
+  "<action_1231>": 152979,
+  "<action_1232>": 152980,
+  "<action_1233>": 152981,
+  "<action_1234>": 152982,
+  "<action_1235>": 152983,
+  "<action_1236>": 152984,
+  "<action_1237>": 152985,
+  "<action_1238>": 152986,
+  "<action_1239>": 152987,
+  "<action_123>": 151871,
+  "<action_1240>": 152988,
+  "<action_1241>": 152989,
+  "<action_1242>": 152990,
+  "<action_1243>": 152991,
+  "<action_1244>": 152992,
+  "<action_1245>": 152993,
+  "<action_1246>": 152994,
+  "<action_1247>": 152995,
+  "<action_1248>": 152996,
+  "<action_1249>": 152997,
+  "<action_124>": 151872,
+  "<action_1250>": 152998,
+  "<action_1251>": 152999,
+  "<action_1252>": 153000,
+  "<action_1253>": 153001,
+  "<action_1254>": 153002,
+  "<action_1255>": 153003,
+  "<action_1256>": 153004,
+  "<action_1257>": 153005,
+  "<action_1258>": 153006,
+  "<action_1259>": 153007,
+  "<action_125>": 151873,
+  "<action_1260>": 153008,
+  "<action_1261>": 153009,
+  "<action_1262>": 153010,
+  "<action_1263>": 153011,
+  "<action_1264>": 153012,
+  "<action_1265>": 153013,
+  "<action_1266>": 153014,
+  "<action_1267>": 153015,
+  "<action_1268>": 153016,
+  "<action_1269>": 153017,
+  "<action_126>": 151874,
+  "<action_1270>": 153018,
+  "<action_1271>": 153019,
+  "<action_1272>": 153020,
+  "<action_1273>": 153021,
+  "<action_1274>": 153022,
+  "<action_1275>": 153023,
+  "<action_1276>": 153024,
+  "<action_1277>": 153025,
+  "<action_1278>": 153026,
+  "<action_1279>": 153027,
+  "<action_127>": 151875,
+  "<action_1280>": 153028,
+  "<action_1281>": 153029,
+  "<action_1282>": 153030,
+  "<action_1283>": 153031,
+  "<action_1284>": 153032,
+  "<action_1285>": 153033,
+  "<action_1286>": 153034,
+  "<action_1287>": 153035,
+  "<action_1288>": 153036,
+  "<action_1289>": 153037,
+  "<action_128>": 151876,
+  "<action_1290>": 153038,
+  "<action_1291>": 153039,
+  "<action_1292>": 153040,
+  "<action_1293>": 153041,
+  "<action_1294>": 153042,
+  "<action_1295>": 153043,
+  "<action_1296>": 153044,
+  "<action_1297>": 153045,
+  "<action_1298>": 153046,
+  "<action_1299>": 153047,
+  "<action_129>": 151877,
+  "<action_12>": 151760,
+  "<action_1300>": 153048,
+  "<action_1301>": 153049,
+  "<action_1302>": 153050,
+  "<action_1303>": 153051,
+  "<action_1304>": 153052,
+  "<action_1305>": 153053,
+  "<action_1306>": 153054,
+  "<action_1307>": 153055,
+  "<action_1308>": 153056,
+  "<action_1309>": 153057,
+  "<action_130>": 151878,
+  "<action_1310>": 153058,
+  "<action_1311>": 153059,
+  "<action_1312>": 153060,
+  "<action_1313>": 153061,
+  "<action_1314>": 153062,
+  "<action_1315>": 153063,
+  "<action_1316>": 153064,
+  "<action_1317>": 153065,
+  "<action_1318>": 153066,
+  "<action_1319>": 153067,
+  "<action_131>": 151879,
+  "<action_1320>": 153068,
+  "<action_1321>": 153069,
+  "<action_1322>": 153070,
+  "<action_1323>": 153071,
+  "<action_1324>": 153072,
+  "<action_1325>": 153073,
+  "<action_1326>": 153074,
+  "<action_1327>": 153075,
+  "<action_1328>": 153076,
+  "<action_1329>": 153077,
+  "<action_132>": 151880,
+  "<action_1330>": 153078,
+  "<action_1331>": 153079,
+  "<action_1332>": 153080,
+  "<action_1333>": 153081,
+  "<action_1334>": 153082,
+  "<action_1335>": 153083,
+  "<action_1336>": 153084,
+  "<action_1337>": 153085,
+  "<action_1338>": 153086,
+  "<action_1339>": 153087,
+  "<action_133>": 151881,
+  "<action_1340>": 153088,
+  "<action_1341>": 153089,
+  "<action_1342>": 153090,
+  "<action_1343>": 153091,
+  "<action_1344>": 153092,
+  "<action_1345>": 153093,
+  "<action_1346>": 153094,
+  "<action_1347>": 153095,
+  "<action_1348>": 153096,
+  "<action_1349>": 153097,
+  "<action_134>": 151882,
+  "<action_1350>": 153098,
+  "<action_1351>": 153099,
+  "<action_1352>": 153100,
+  "<action_1353>": 153101,
+  "<action_1354>": 153102,
+  "<action_1355>": 153103,
+  "<action_1356>": 153104,
+  "<action_1357>": 153105,
+  "<action_1358>": 153106,
+  "<action_1359>": 153107,
+  "<action_135>": 151883,
+  "<action_1360>": 153108,
+  "<action_1361>": 153109,
+  "<action_1362>": 153110,
+  "<action_1363>": 153111,
+  "<action_1364>": 153112,
+  "<action_1365>": 153113,
+  "<action_1366>": 153114,
+  "<action_1367>": 153115,
+  "<action_1368>": 153116,
+  "<action_1369>": 153117,
+  "<action_136>": 151884,
+  "<action_1370>": 153118,
+  "<action_1371>": 153119,
+  "<action_1372>": 153120,
+  "<action_1373>": 153121,
+  "<action_1374>": 153122,
+  "<action_1375>": 153123,
+  "<action_1376>": 153124,
+  "<action_1377>": 153125,
+  "<action_1378>": 153126,
+  "<action_1379>": 153127,
+  "<action_137>": 151885,
+  "<action_1380>": 153128,
+  "<action_1381>": 153129,
+  "<action_1382>": 153130,
+  "<action_1383>": 153131,
+  "<action_1384>": 153132,
+  "<action_1385>": 153133,
+  "<action_1386>": 153134,
+  "<action_1387>": 153135,
+  "<action_1388>": 153136,
+  "<action_1389>": 153137,
+  "<action_138>": 151886,
+  "<action_1390>": 153138,
+  "<action_1391>": 153139,
+  "<action_1392>": 153140,
+  "<action_1393>": 153141,
+  "<action_1394>": 153142,
+  "<action_1395>": 153143,
+  "<action_1396>": 153144,
+  "<action_1397>": 153145,
+  "<action_1398>": 153146,
+  "<action_1399>": 153147,
+  "<action_139>": 151887,
+  "<action_13>": 151761,
+  "<action_1400>": 153148,
+  "<action_1401>": 153149,
+  "<action_1402>": 153150,
+  "<action_1403>": 153151,
+  "<action_1404>": 153152,
+  "<action_1405>": 153153,
+  "<action_1406>": 153154,
+  "<action_1407>": 153155,
+  "<action_1408>": 153156,
+  "<action_1409>": 153157,
+  "<action_140>": 151888,
+  "<action_1410>": 153158,
+  "<action_1411>": 153159,
+  "<action_1412>": 153160,
+  "<action_1413>": 153161,
+  "<action_1414>": 153162,
+  "<action_1415>": 153163,
+  "<action_1416>": 153164,
+  "<action_1417>": 153165,
+  "<action_1418>": 153166,
+  "<action_1419>": 153167,
+  "<action_141>": 151889,
+  "<action_1420>": 153168,
+  "<action_1421>": 153169,
+  "<action_1422>": 153170,
+  "<action_1423>": 153171,
+  "<action_1424>": 153172,
+  "<action_1425>": 153173,
+  "<action_1426>": 153174,
+  "<action_1427>": 153175,
+  "<action_1428>": 153176,
+  "<action_1429>": 153177,
+  "<action_142>": 151890,
+  "<action_1430>": 153178,
+  "<action_1431>": 153179,
+  "<action_1432>": 153180,
+  "<action_1433>": 153181,
+  "<action_1434>": 153182,
+  "<action_1435>": 153183,
+  "<action_1436>": 153184,
+  "<action_1437>": 153185,
+  "<action_1438>": 153186,
+  "<action_1439>": 153187,
+  "<action_143>": 151891,
+  "<action_1440>": 153188,
+  "<action_1441>": 153189,
+  "<action_1442>": 153190,
+  "<action_1443>": 153191,
+  "<action_1444>": 153192,
+  "<action_1445>": 153193,
+  "<action_1446>": 153194,
+  "<action_1447>": 153195,
+  "<action_1448>": 153196,
+  "<action_1449>": 153197,
+  "<action_144>": 151892,
+  "<action_1450>": 153198,
+  "<action_1451>": 153199,
+  "<action_1452>": 153200,
+  "<action_1453>": 153201,
+  "<action_1454>": 153202,
+  "<action_1455>": 153203,
+  "<action_1456>": 153204,
+  "<action_1457>": 153205,
+  "<action_1458>": 153206,
+  "<action_1459>": 153207,
+  "<action_145>": 151893,
+  "<action_1460>": 153208,
+  "<action_1461>": 153209,
+  "<action_1462>": 153210,
+  "<action_1463>": 153211,
+  "<action_1464>": 153212,
+  "<action_1465>": 153213,
+  "<action_1466>": 153214,
+  "<action_1467>": 153215,
+  "<action_1468>": 153216,
+  "<action_1469>": 153217,
+  "<action_146>": 151894,
+  "<action_1470>": 153218,
+  "<action_1471>": 153219,
+  "<action_1472>": 153220,
+  "<action_1473>": 153221,
+  "<action_1474>": 153222,
+  "<action_1475>": 153223,
+  "<action_1476>": 153224,
+  "<action_1477>": 153225,
+  "<action_1478>": 153226,
+  "<action_1479>": 153227,
+  "<action_147>": 151895,
+  "<action_1480>": 153228,
+  "<action_1481>": 153229,
+  "<action_1482>": 153230,
+  "<action_1483>": 153231,
+  "<action_1484>": 153232,
+  "<action_1485>": 153233,
+  "<action_1486>": 153234,
+  "<action_1487>": 153235,
+  "<action_1488>": 153236,
+  "<action_1489>": 153237,
+  "<action_148>": 151896,
+  "<action_1490>": 153238,
+  "<action_1491>": 153239,
+  "<action_1492>": 153240,
+  "<action_1493>": 153241,
+  "<action_1494>": 153242,
+  "<action_1495>": 153243,
+  "<action_1496>": 153244,
+  "<action_1497>": 153245,
+  "<action_1498>": 153246,
+  "<action_1499>": 153247,
+  "<action_149>": 151897,
+  "<action_14>": 151762,
+  "<action_1500>": 153248,
+  "<action_1501>": 153249,
+  "<action_1502>": 153250,
+  "<action_1503>": 153251,
+  "<action_1504>": 153252,
+  "<action_1505>": 153253,
+  "<action_1506>": 153254,
+  "<action_1507>": 153255,
+  "<action_1508>": 153256,
+  "<action_1509>": 153257,
+  "<action_150>": 151898,
+  "<action_1510>": 153258,
+  "<action_1511>": 153259,
+  "<action_1512>": 153260,
+  "<action_1513>": 153261,
+  "<action_1514>": 153262,
+  "<action_1515>": 153263,
+  "<action_1516>": 153264,
+  "<action_1517>": 153265,
+  "<action_1518>": 153266,
+  "<action_1519>": 153267,
+  "<action_151>": 151899,
+  "<action_1520>": 153268,
+  "<action_1521>": 153269,
+  "<action_1522>": 153270,
+  "<action_1523>": 153271,
+  "<action_1524>": 153272,
+  "<action_1525>": 153273,
+  "<action_1526>": 153274,
+  "<action_1527>": 153275,
+  "<action_1528>": 153276,
+  "<action_1529>": 153277,
+  "<action_152>": 151900,
+  "<action_1530>": 153278,
+  "<action_1531>": 153279,
+  "<action_1532>": 153280,
+  "<action_1533>": 153281,
+  "<action_1534>": 153282,
+  "<action_1535>": 153283,
+  "<action_1536>": 153284,
+  "<action_1537>": 153285,
+  "<action_1538>": 153286,
+  "<action_1539>": 153287,
+  "<action_153>": 151901,
+  "<action_1540>": 153288,
+  "<action_1541>": 153289,
+  "<action_1542>": 153290,
+  "<action_1543>": 153291,
+  "<action_1544>": 153292,
+  "<action_1545>": 153293,
+  "<action_1546>": 153294,
+  "<action_1547>": 153295,
+  "<action_1548>": 153296,
+  "<action_1549>": 153297,
+  "<action_154>": 151902,
+  "<action_1550>": 153298,
+  "<action_1551>": 153299,
+  "<action_1552>": 153300,
+  "<action_1553>": 153301,
+  "<action_1554>": 153302,
+  "<action_1555>": 153303,
+  "<action_1556>": 153304,
+  "<action_1557>": 153305,
+  "<action_1558>": 153306,
+  "<action_1559>": 153307,
+  "<action_155>": 151903,
+  "<action_1560>": 153308,
+  "<action_1561>": 153309,
+  "<action_1562>": 153310,
+  "<action_1563>": 153311,
+  "<action_1564>": 153312,
+  "<action_1565>": 153313,
+  "<action_1566>": 153314,
+  "<action_1567>": 153315,
+  "<action_1568>": 153316,
+  "<action_1569>": 153317,
+  "<action_156>": 151904,
+  "<action_1570>": 153318,
+  "<action_1571>": 153319,
+  "<action_1572>": 153320,
+  "<action_1573>": 153321,
+  "<action_1574>": 153322,
+  "<action_1575>": 153323,
+  "<action_1576>": 153324,
+  "<action_1577>": 153325,
+  "<action_1578>": 153326,
+  "<action_1579>": 153327,
+  "<action_157>": 151905,
+  "<action_1580>": 153328,
+  "<action_1581>": 153329,
+  "<action_1582>": 153330,
+  "<action_1583>": 153331,
+  "<action_1584>": 153332,
+  "<action_1585>": 153333,
+  "<action_1586>": 153334,
+  "<action_1587>": 153335,
+  "<action_1588>": 153336,
+  "<action_1589>": 153337,
+  "<action_158>": 151906,
+  "<action_1590>": 153338,
+  "<action_1591>": 153339,
+  "<action_1592>": 153340,
+  "<action_1593>": 153341,
+  "<action_1594>": 153342,
+  "<action_1595>": 153343,
+  "<action_1596>": 153344,
+  "<action_1597>": 153345,
+  "<action_1598>": 153346,
+  "<action_1599>": 153347,
+  "<action_159>": 151907,
+  "<action_15>": 151763,
+  "<action_1600>": 153348,
+  "<action_1601>": 153349,
+  "<action_1602>": 153350,
+  "<action_1603>": 153351,
+  "<action_1604>": 153352,
+  "<action_1605>": 153353,
+  "<action_1606>": 153354,
+  "<action_1607>": 153355,
+  "<action_1608>": 153356,
+  "<action_1609>": 153357,
+  "<action_160>": 151908,
+  "<action_1610>": 153358,
+  "<action_1611>": 153359,
+  "<action_1612>": 153360,
+  "<action_1613>": 153361,
+  "<action_1614>": 153362,
+  "<action_1615>": 153363,
+  "<action_1616>": 153364,
+  "<action_1617>": 153365,
+  "<action_1618>": 153366,
+  "<action_1619>": 153367,
+  "<action_161>": 151909,
+  "<action_1620>": 153368,
+  "<action_1621>": 153369,
+  "<action_1622>": 153370,
+  "<action_1623>": 153371,
+  "<action_1624>": 153372,
+  "<action_1625>": 153373,
+  "<action_1626>": 153374,
+  "<action_1627>": 153375,
+  "<action_1628>": 153376,
+  "<action_1629>": 153377,
+  "<action_162>": 151910,
+  "<action_1630>": 153378,
+  "<action_1631>": 153379,
+  "<action_1632>": 153380,
+  "<action_1633>": 153381,
+  "<action_1634>": 153382,
+  "<action_1635>": 153383,
+  "<action_1636>": 153384,
+  "<action_1637>": 153385,
+  "<action_1638>": 153386,
+  "<action_1639>": 153387,
+  "<action_163>": 151911,
+  "<action_1640>": 153388,
+  "<action_1641>": 153389,
+  "<action_1642>": 153390,
+  "<action_1643>": 153391,
+  "<action_1644>": 153392,
+  "<action_1645>": 153393,
+  "<action_1646>": 153394,
+  "<action_1647>": 153395,
+  "<action_1648>": 153396,
+  "<action_1649>": 153397,
+  "<action_164>": 151912,
+  "<action_1650>": 153398,
+  "<action_1651>": 153399,
+  "<action_1652>": 153400,
+  "<action_1653>": 153401,
+  "<action_1654>": 153402,
+  "<action_1655>": 153403,
+  "<action_1656>": 153404,
+  "<action_1657>": 153405,
+  "<action_1658>": 153406,
+  "<action_1659>": 153407,
+  "<action_165>": 151913,
+  "<action_1660>": 153408,
+  "<action_1661>": 153409,
+  "<action_1662>": 153410,
+  "<action_1663>": 153411,
+  "<action_1664>": 153412,
+  "<action_1665>": 153413,
+  "<action_1666>": 153414,
+  "<action_1667>": 153415,
+  "<action_1668>": 153416,
+  "<action_1669>": 153417,
+  "<action_166>": 151914,
+  "<action_1670>": 153418,
+  "<action_1671>": 153419,
+  "<action_1672>": 153420,
+  "<action_1673>": 153421,
+  "<action_1674>": 153422,
+  "<action_1675>": 153423,
+  "<action_1676>": 153424,
+  "<action_1677>": 153425,
+  "<action_1678>": 153426,
+  "<action_1679>": 153427,
+  "<action_167>": 151915,
+  "<action_1680>": 153428,
+  "<action_1681>": 153429,
+  "<action_1682>": 153430,
+  "<action_1683>": 153431,
+  "<action_1684>": 153432,
+  "<action_1685>": 153433,
+  "<action_1686>": 153434,
+  "<action_1687>": 153435,
+  "<action_1688>": 153436,
+  "<action_1689>": 153437,
+  "<action_168>": 151916,
+  "<action_1690>": 153438,
+  "<action_1691>": 153439,
+  "<action_1692>": 153440,
+  "<action_1693>": 153441,
+  "<action_1694>": 153442,
+  "<action_1695>": 153443,
+  "<action_1696>": 153444,
+  "<action_1697>": 153445,
+  "<action_1698>": 153446,
+  "<action_1699>": 153447,
+  "<action_169>": 151917,
+  "<action_16>": 151764,
+  "<action_1700>": 153448,
+  "<action_1701>": 153449,
+  "<action_1702>": 153450,
+  "<action_1703>": 153451,
+  "<action_1704>": 153452,
+  "<action_1705>": 153453,
+  "<action_1706>": 153454,
+  "<action_1707>": 153455,
+  "<action_1708>": 153456,
+  "<action_1709>": 153457,
+  "<action_170>": 151918,
+  "<action_1710>": 153458,
+  "<action_1711>": 153459,
+  "<action_1712>": 153460,
+  "<action_1713>": 153461,
+  "<action_1714>": 153462,
+  "<action_1715>": 153463,
+  "<action_1716>": 153464,
+  "<action_1717>": 153465,
+  "<action_1718>": 153466,
+  "<action_1719>": 153467,
+  "<action_171>": 151919,
+  "<action_1720>": 153468,
+  "<action_1721>": 153469,
+  "<action_1722>": 153470,
+  "<action_1723>": 153471,
+  "<action_1724>": 153472,
+  "<action_1725>": 153473,
+  "<action_1726>": 153474,
+  "<action_1727>": 153475,
+  "<action_1728>": 153476,
+  "<action_1729>": 153477,
+  "<action_172>": 151920,
+  "<action_1730>": 153478,
+  "<action_1731>": 153479,
+  "<action_1732>": 153480,
+  "<action_1733>": 153481,
+  "<action_1734>": 153482,
+  "<action_1735>": 153483,
+  "<action_1736>": 153484,
+  "<action_1737>": 153485,
+  "<action_1738>": 153486,
+  "<action_1739>": 153487,
+  "<action_173>": 151921,
+  "<action_1740>": 153488,
+  "<action_1741>": 153489,
+  "<action_1742>": 153490,
+  "<action_1743>": 153491,
+  "<action_1744>": 153492,
+  "<action_1745>": 153493,
+  "<action_1746>": 153494,
+  "<action_1747>": 153495,
+  "<action_1748>": 153496,
+  "<action_1749>": 153497,
+  "<action_174>": 151922,
+  "<action_1750>": 153498,
+  "<action_1751>": 153499,
+  "<action_1752>": 153500,
+  "<action_1753>": 153501,
+  "<action_1754>": 153502,
+  "<action_1755>": 153503,
+  "<action_1756>": 153504,
+  "<action_1757>": 153505,
+  "<action_1758>": 153506,
+  "<action_1759>": 153507,
+  "<action_175>": 151923,
+  "<action_1760>": 153508,
+  "<action_1761>": 153509,
+  "<action_1762>": 153510,
+  "<action_1763>": 153511,
+  "<action_1764>": 153512,
+  "<action_1765>": 153513,
+  "<action_1766>": 153514,
+  "<action_1767>": 153515,
+  "<action_1768>": 153516,
+  "<action_1769>": 153517,
+  "<action_176>": 151924,
+  "<action_1770>": 153518,
+  "<action_1771>": 153519,
+  "<action_1772>": 153520,
+  "<action_1773>": 153521,
+  "<action_1774>": 153522,
+  "<action_1775>": 153523,
+  "<action_1776>": 153524,
+  "<action_1777>": 153525,
+  "<action_1778>": 153526,
+  "<action_1779>": 153527,
+  "<action_177>": 151925,
+  "<action_1780>": 153528,
+  "<action_1781>": 153529,
+  "<action_1782>": 153530,
+  "<action_1783>": 153531,
+  "<action_1784>": 153532,
+  "<action_1785>": 153533,
+  "<action_1786>": 153534,
+  "<action_1787>": 153535,
+  "<action_1788>": 153536,
+  "<action_1789>": 153537,
+  "<action_178>": 151926,
+  "<action_1790>": 153538,
+  "<action_1791>": 153539,
+  "<action_1792>": 153540,
+  "<action_1793>": 153541,
+  "<action_1794>": 153542,
+  "<action_1795>": 153543,
+  "<action_1796>": 153544,
+  "<action_1797>": 153545,
+  "<action_1798>": 153546,
+  "<action_1799>": 153547,
+  "<action_179>": 151927,
+  "<action_17>": 151765,
+  "<action_1800>": 153548,
+  "<action_1801>": 153549,
+  "<action_1802>": 153550,
+  "<action_1803>": 153551,
+  "<action_1804>": 153552,
+  "<action_1805>": 153553,
+  "<action_1806>": 153554,
+  "<action_1807>": 153555,
+  "<action_1808>": 153556,
+  "<action_1809>": 153557,
+  "<action_180>": 151928,
+  "<action_1810>": 153558,
+  "<action_1811>": 153559,
+  "<action_1812>": 153560,
+  "<action_1813>": 153561,
+  "<action_1814>": 153562,
+  "<action_1815>": 153563,
+  "<action_1816>": 153564,
+  "<action_1817>": 153565,
+  "<action_1818>": 153566,
+  "<action_1819>": 153567,
+  "<action_181>": 151929,
+  "<action_1820>": 153568,
+  "<action_1821>": 153569,
+  "<action_1822>": 153570,
+  "<action_1823>": 153571,
+  "<action_1824>": 153572,
+  "<action_1825>": 153573,
+  "<action_1826>": 153574,
+  "<action_1827>": 153575,
+  "<action_1828>": 153576,
+  "<action_1829>": 153577,
+  "<action_182>": 151930,
+  "<action_1830>": 153578,
+  "<action_1831>": 153579,
+  "<action_1832>": 153580,
+  "<action_1833>": 153581,
+  "<action_1834>": 153582,
+  "<action_1835>": 153583,
+  "<action_1836>": 153584,
+  "<action_1837>": 153585,
+  "<action_1838>": 153586,
+  "<action_1839>": 153587,
+  "<action_183>": 151931,
+  "<action_1840>": 153588,
+  "<action_1841>": 153589,
+  "<action_1842>": 153590,
+  "<action_1843>": 153591,
+  "<action_1844>": 153592,
+  "<action_1845>": 153593,
+  "<action_1846>": 153594,
+  "<action_1847>": 153595,
+  "<action_1848>": 153596,
+  "<action_1849>": 153597,
+  "<action_184>": 151932,
+  "<action_1850>": 153598,
+  "<action_1851>": 153599,
+  "<action_1852>": 153600,
+  "<action_1853>": 153601,
+  "<action_1854>": 153602,
+  "<action_1855>": 153603,
+  "<action_1856>": 153604,
+  "<action_1857>": 153605,
+  "<action_1858>": 153606,
+  "<action_1859>": 153607,
+  "<action_185>": 151933,
+  "<action_1860>": 153608,
+  "<action_1861>": 153609,
+  "<action_1862>": 153610,
+  "<action_1863>": 153611,
+  "<action_1864>": 153612,
+  "<action_1865>": 153613,
+  "<action_1866>": 153614,
+  "<action_1867>": 153615,
+  "<action_1868>": 153616,
+  "<action_1869>": 153617,
+  "<action_186>": 151934,
+  "<action_1870>": 153618,
+  "<action_1871>": 153619,
+  "<action_1872>": 153620,
+  "<action_1873>": 153621,
+  "<action_1874>": 153622,
+  "<action_1875>": 153623,
+  "<action_1876>": 153624,
+  "<action_1877>": 153625,
+  "<action_1878>": 153626,
+  "<action_1879>": 153627,
+  "<action_187>": 151935,
+  "<action_1880>": 153628,
+  "<action_1881>": 153629,
+  "<action_1882>": 153630,
+  "<action_1883>": 153631,
+  "<action_1884>": 153632,
+  "<action_1885>": 153633,
+  "<action_1886>": 153634,
+  "<action_1887>": 153635,
+  "<action_1888>": 153636,
+  "<action_1889>": 153637,
+  "<action_188>": 151936,
+  "<action_1890>": 153638,
+  "<action_1891>": 153639,
+  "<action_1892>": 153640,
+  "<action_1893>": 153641,
+  "<action_1894>": 153642,
+  "<action_1895>": 153643,
+  "<action_1896>": 153644,
+  "<action_1897>": 153645,
+  "<action_1898>": 153646,
+  "<action_1899>": 153647,
+  "<action_189>": 151937,
+  "<action_18>": 151766,
+  "<action_1900>": 153648,
+  "<action_1901>": 153649,
+  "<action_1902>": 153650,
+  "<action_1903>": 153651,
+  "<action_1904>": 153652,
+  "<action_1905>": 153653,
+  "<action_1906>": 153654,
+  "<action_1907>": 153655,
+  "<action_1908>": 153656,
+  "<action_1909>": 153657,
+  "<action_190>": 151938,
+  "<action_1910>": 153658,
+  "<action_1911>": 153659,
+  "<action_1912>": 153660,
+  "<action_1913>": 153661,
+  "<action_1914>": 153662,
+  "<action_1915>": 153663,
+  "<action_1916>": 153664,
+  "<action_1917>": 153665,
+  "<action_1918>": 153666,
+  "<action_1919>": 153667,
+  "<action_191>": 151939,
+  "<action_1920>": 153668,
+  "<action_1921>": 153669,
+  "<action_1922>": 153670,
+  "<action_1923>": 153671,
+  "<action_1924>": 153672,
+  "<action_1925>": 153673,
+  "<action_1926>": 153674,
+  "<action_1927>": 153675,
+  "<action_1928>": 153676,
+  "<action_1929>": 153677,
+  "<action_192>": 151940,
+  "<action_1930>": 153678,
+  "<action_1931>": 153679,
+  "<action_1932>": 153680,
+  "<action_1933>": 153681,
+  "<action_1934>": 153682,
+  "<action_1935>": 153683,
+  "<action_1936>": 153684,
+  "<action_1937>": 153685,
+  "<action_1938>": 153686,
+  "<action_1939>": 153687,
+  "<action_193>": 151941,
+  "<action_1940>": 153688,
+  "<action_1941>": 153689,
+  "<action_1942>": 153690,
+  "<action_1943>": 153691,
+  "<action_1944>": 153692,
+  "<action_1945>": 153693,
+  "<action_1946>": 153694,
+  "<action_1947>": 153695,
+  "<action_1948>": 153696,
+  "<action_1949>": 153697,
+  "<action_194>": 151942,
+  "<action_1950>": 153698,
+  "<action_1951>": 153699,
+  "<action_1952>": 153700,
+  "<action_1953>": 153701,
+  "<action_1954>": 153702,
+  "<action_1955>": 153703,
+  "<action_1956>": 153704,
+  "<action_1957>": 153705,
+  "<action_1958>": 153706,
+  "<action_1959>": 153707,
+  "<action_195>": 151943,
+  "<action_1960>": 153708,
+  "<action_1961>": 153709,
+  "<action_1962>": 153710,
+  "<action_1963>": 153711,
+  "<action_1964>": 153712,
+  "<action_1965>": 153713,
+  "<action_1966>": 153714,
+  "<action_1967>": 153715,
+  "<action_1968>": 153716,
+  "<action_1969>": 153717,
+  "<action_196>": 151944,
+  "<action_1970>": 153718,
+  "<action_1971>": 153719,
+  "<action_1972>": 153720,
+  "<action_1973>": 153721,
+  "<action_1974>": 153722,
+  "<action_1975>": 153723,
+  "<action_1976>": 153724,
+  "<action_1977>": 153725,
+  "<action_1978>": 153726,
+  "<action_1979>": 153727,
+  "<action_197>": 151945,
+  "<action_1980>": 153728,
+  "<action_1981>": 153729,
+  "<action_1982>": 153730,
+  "<action_1983>": 153731,
+  "<action_1984>": 153732,
+  "<action_1985>": 153733,
+  "<action_1986>": 153734,
+  "<action_1987>": 153735,
+  "<action_1988>": 153736,
+  "<action_1989>": 153737,
+  "<action_198>": 151946,
+  "<action_1990>": 153738,
+  "<action_1991>": 153739,
+  "<action_1992>": 153740,
+  "<action_1993>": 153741,
+  "<action_1994>": 153742,
+  "<action_1995>": 153743,
+  "<action_1996>": 153744,
+  "<action_1997>": 153745,
+  "<action_1998>": 153746,
+  "<action_1999>": 153747,
+  "<action_199>": 151947,
+  "<action_19>": 151767,
+  "<action_1>": 151749,
+  "<action_2000>": 153748,
+  "<action_2001>": 153749,
+  "<action_2002>": 153750,
+  "<action_2003>": 153751,
+  "<action_2004>": 153752,
+  "<action_2005>": 153753,
+  "<action_2006>": 153754,
+  "<action_2007>": 153755,
+  "<action_2008>": 153756,
+  "<action_2009>": 153757,
+  "<action_200>": 151948,
+  "<action_2010>": 153758,
+  "<action_2011>": 153759,
+  "<action_2012>": 153760,
+  "<action_2013>": 153761,
+  "<action_2014>": 153762,
+  "<action_2015>": 153763,
+  "<action_2016>": 153764,
+  "<action_2017>": 153765,
+  "<action_2018>": 153766,
+  "<action_2019>": 153767,
+  "<action_201>": 151949,
+  "<action_2020>": 153768,
+  "<action_2021>": 153769,
+  "<action_2022>": 153770,
+  "<action_2023>": 153771,
+  "<action_2024>": 153772,
+  "<action_2025>": 153773,
+  "<action_2026>": 153774,
+  "<action_2027>": 153775,
+  "<action_2028>": 153776,
+  "<action_2029>": 153777,
+  "<action_202>": 151950,
+  "<action_2030>": 153778,
+  "<action_2031>": 153779,
+  "<action_2032>": 153780,
+  "<action_2033>": 153781,
+  "<action_2034>": 153782,
+  "<action_2035>": 153783,
+  "<action_2036>": 153784,
+  "<action_2037>": 153785,
+  "<action_2038>": 153786,
+  "<action_2039>": 153787,
+  "<action_203>": 151951,
+  "<action_2040>": 153788,
+  "<action_2041>": 153789,
+  "<action_2042>": 153790,
+  "<action_2043>": 153791,
+  "<action_2044>": 153792,
+  "<action_2045>": 153793,
+  "<action_2046>": 153794,
+  "<action_2047>": 153795,
+  "<action_204>": 151952,
+  "<action_205>": 151953,
+  "<action_206>": 151954,
+  "<action_207>": 151955,
+  "<action_208>": 151956,
+  "<action_209>": 151957,
+  "<action_20>": 151768,
+  "<action_210>": 151958,
+  "<action_211>": 151959,
+  "<action_212>": 151960,
+  "<action_213>": 151961,
+  "<action_214>": 151962,
+  "<action_215>": 151963,
+  "<action_216>": 151964,
+  "<action_217>": 151965,
+  "<action_218>": 151966,
+  "<action_219>": 151967,
+  "<action_21>": 151769,
+  "<action_220>": 151968,
+  "<action_221>": 151969,
+  "<action_222>": 151970,
+  "<action_223>": 151971,
+  "<action_224>": 151972,
+  "<action_225>": 151973,
+  "<action_226>": 151974,
+  "<action_227>": 151975,
+  "<action_228>": 151976,
+  "<action_229>": 151977,
+  "<action_22>": 151770,
+  "<action_230>": 151978,
+  "<action_231>": 151979,
+  "<action_232>": 151980,
+  "<action_233>": 151981,
+  "<action_234>": 151982,
+  "<action_235>": 151983,
+  "<action_236>": 151984,
+  "<action_237>": 151985,
+  "<action_238>": 151986,
+  "<action_239>": 151987,
+  "<action_23>": 151771,
+  "<action_240>": 151988,
+  "<action_241>": 151989,
+  "<action_242>": 151990,
+  "<action_243>": 151991,
+  "<action_244>": 151992,
+  "<action_245>": 151993,
+  "<action_246>": 151994,
+  "<action_247>": 151995,
+  "<action_248>": 151996,
+  "<action_249>": 151997,
+  "<action_24>": 151772,
+  "<action_250>": 151998,
+  "<action_251>": 151999,
+  "<action_252>": 152000,
+  "<action_253>": 152001,
+  "<action_254>": 152002,
+  "<action_255>": 152003,
+  "<action_256>": 152004,
+  "<action_257>": 152005,
+  "<action_258>": 152006,
+  "<action_259>": 152007,
+  "<action_25>": 151773,
+  "<action_260>": 152008,
+  "<action_261>": 152009,
+  "<action_262>": 152010,
+  "<action_263>": 152011,
+  "<action_264>": 152012,
+  "<action_265>": 152013,
+  "<action_266>": 152014,
+  "<action_267>": 152015,
+  "<action_268>": 152016,
+  "<action_269>": 152017,
+  "<action_26>": 151774,
+  "<action_270>": 152018,
+  "<action_271>": 152019,
+  "<action_272>": 152020,
+  "<action_273>": 152021,
+  "<action_274>": 152022,
+  "<action_275>": 152023,
+  "<action_276>": 152024,
+  "<action_277>": 152025,
+  "<action_278>": 152026,
+  "<action_279>": 152027,
+  "<action_27>": 151775,
+  "<action_280>": 152028,
+  "<action_281>": 152029,
+  "<action_282>": 152030,
+  "<action_283>": 152031,
+  "<action_284>": 152032,
+  "<action_285>": 152033,
+  "<action_286>": 152034,
+  "<action_287>": 152035,
+  "<action_288>": 152036,
+  "<action_289>": 152037,
+  "<action_28>": 151776,
+  "<action_290>": 152038,
+  "<action_291>": 152039,
+  "<action_292>": 152040,
+  "<action_293>": 152041,
+  "<action_294>": 152042,
+  "<action_295>": 152043,
+  "<action_296>": 152044,
+  "<action_297>": 152045,
+  "<action_298>": 152046,
+  "<action_299>": 152047,
+  "<action_29>": 151777,
+  "<action_2>": 151750,
+  "<action_300>": 152048,
+  "<action_301>": 152049,
+  "<action_302>": 152050,
+  "<action_303>": 152051,
+  "<action_304>": 152052,
+  "<action_305>": 152053,
+  "<action_306>": 152054,
+  "<action_307>": 152055,
+  "<action_308>": 152056,
+  "<action_309>": 152057,
+  "<action_30>": 151778,
+  "<action_310>": 152058,
+  "<action_311>": 152059,
+  "<action_312>": 152060,
+  "<action_313>": 152061,
+  "<action_314>": 152062,
+  "<action_315>": 152063,
+  "<action_316>": 152064,
+  "<action_317>": 152065,
+  "<action_318>": 152066,
+  "<action_319>": 152067,
+  "<action_31>": 151779,
+  "<action_320>": 152068,
+  "<action_321>": 152069,
+  "<action_322>": 152070,
+  "<action_323>": 152071,
+  "<action_324>": 152072,
+  "<action_325>": 152073,
+  "<action_326>": 152074,
+  "<action_327>": 152075,
+  "<action_328>": 152076,
+  "<action_329>": 152077,
+  "<action_32>": 151780,
+  "<action_330>": 152078,
+  "<action_331>": 152079,
+  "<action_332>": 152080,
+  "<action_333>": 152081,
+  "<action_334>": 152082,
+  "<action_335>": 152083,
+  "<action_336>": 152084,
+  "<action_337>": 152085,
+  "<action_338>": 152086,
+  "<action_339>": 152087,
+  "<action_33>": 151781,
+  "<action_340>": 152088,
+  "<action_341>": 152089,
+  "<action_342>": 152090,
+  "<action_343>": 152091,
+  "<action_344>": 152092,
+  "<action_345>": 152093,
+  "<action_346>": 152094,
+  "<action_347>": 152095,
+  "<action_348>": 152096,
+  "<action_349>": 152097,
+  "<action_34>": 151782,
+  "<action_350>": 152098,
+  "<action_351>": 152099,
+  "<action_352>": 152100,
+  "<action_353>": 152101,
+  "<action_354>": 152102,
+  "<action_355>": 152103,
+  "<action_356>": 152104,
+  "<action_357>": 152105,
+  "<action_358>": 152106,
+  "<action_359>": 152107,
+  "<action_35>": 151783,
+  "<action_360>": 152108,
+  "<action_361>": 152109,
+  "<action_362>": 152110,
+  "<action_363>": 152111,
+  "<action_364>": 152112,
+  "<action_365>": 152113,
+  "<action_366>": 152114,
+  "<action_367>": 152115,
+  "<action_368>": 152116,
+  "<action_369>": 152117,
+  "<action_36>": 151784,
+  "<action_370>": 152118,
+  "<action_371>": 152119,
+  "<action_372>": 152120,
+  "<action_373>": 152121,
+  "<action_374>": 152122,
+  "<action_375>": 152123,
+  "<action_376>": 152124,
+  "<action_377>": 152125,
+  "<action_378>": 152126,
+  "<action_379>": 152127,
+  "<action_37>": 151785,
+  "<action_380>": 152128,
+  "<action_381>": 152129,
+  "<action_382>": 152130,
+  "<action_383>": 152131,
+  "<action_384>": 152132,
+  "<action_385>": 152133,
+  "<action_386>": 152134,
+  "<action_387>": 152135,
+  "<action_388>": 152136,
+  "<action_389>": 152137,
+  "<action_38>": 151786,
+  "<action_390>": 152138,
+  "<action_391>": 152139,
+  "<action_392>": 152140,
+  "<action_393>": 152141,
+  "<action_394>": 152142,
+  "<action_395>": 152143,
+  "<action_396>": 152144,
+  "<action_397>": 152145,
+  "<action_398>": 152146,
+  "<action_399>": 152147,
+  "<action_39>": 151787,
+  "<action_3>": 151751,
+  "<action_400>": 152148,
+  "<action_401>": 152149,
+  "<action_402>": 152150,
+  "<action_403>": 152151,
+  "<action_404>": 152152,
+  "<action_405>": 152153,
+  "<action_406>": 152154,
+  "<action_407>": 152155,
+  "<action_408>": 152156,
+  "<action_409>": 152157,
+  "<action_40>": 151788,
+  "<action_410>": 152158,
+  "<action_411>": 152159,
+  "<action_412>": 152160,
+  "<action_413>": 152161,
+  "<action_414>": 152162,
+  "<action_415>": 152163,
+  "<action_416>": 152164,
+  "<action_417>": 152165,
+  "<action_418>": 152166,
+  "<action_419>": 152167,
+  "<action_41>": 151789,
+  "<action_420>": 152168,
+  "<action_421>": 152169,
+  "<action_422>": 152170,
+  "<action_423>": 152171,
+  "<action_424>": 152172,
+  "<action_425>": 152173,
+  "<action_426>": 152174,
+  "<action_427>": 152175,
+  "<action_428>": 152176,
+  "<action_429>": 152177,
+  "<action_42>": 151790,
+  "<action_430>": 152178,
+  "<action_431>": 152179,
+  "<action_432>": 152180,
+  "<action_433>": 152181,
+  "<action_434>": 152182,
+  "<action_435>": 152183,
+  "<action_436>": 152184,
+  "<action_437>": 152185,
+  "<action_438>": 152186,
+  "<action_439>": 152187,
+  "<action_43>": 151791,
+  "<action_440>": 152188,
+  "<action_441>": 152189,
+  "<action_442>": 152190,
+  "<action_443>": 152191,
+  "<action_444>": 152192,
+  "<action_445>": 152193,
+  "<action_446>": 152194,
+  "<action_447>": 152195,
+  "<action_448>": 152196,
+  "<action_449>": 152197,
+  "<action_44>": 151792,
+  "<action_450>": 152198,
+  "<action_451>": 152199,
+  "<action_452>": 152200,
+  "<action_453>": 152201,
+  "<action_454>": 152202,
+  "<action_455>": 152203,
+  "<action_456>": 152204,
+  "<action_457>": 152205,
+  "<action_458>": 152206,
+  "<action_459>": 152207,
+  "<action_45>": 151793,
+  "<action_460>": 152208,
+  "<action_461>": 152209,
+  "<action_462>": 152210,
+  "<action_463>": 152211,
+  "<action_464>": 152212,
+  "<action_465>": 152213,
+  "<action_466>": 152214,
+  "<action_467>": 152215,
+  "<action_468>": 152216,
+  "<action_469>": 152217,
+  "<action_46>": 151794,
+  "<action_470>": 152218,
+  "<action_471>": 152219,
+  "<action_472>": 152220,
+  "<action_473>": 152221,
+  "<action_474>": 152222,
+  "<action_475>": 152223,
+  "<action_476>": 152224,
+  "<action_477>": 152225,
+  "<action_478>": 152226,
+  "<action_479>": 152227,
+  "<action_47>": 151795,
+  "<action_480>": 152228,
+  "<action_481>": 152229,
+  "<action_482>": 152230,
+  "<action_483>": 152231,
+  "<action_484>": 152232,
+  "<action_485>": 152233,
+  "<action_486>": 152234,
+  "<action_487>": 152235,
+  "<action_488>": 152236,
+  "<action_489>": 152237,
+  "<action_48>": 151796,
+  "<action_490>": 152238,
+  "<action_491>": 152239,
+  "<action_492>": 152240,
+  "<action_493>": 152241,
+  "<action_494>": 152242,
+  "<action_495>": 152243,
+  "<action_496>": 152244,
+  "<action_497>": 152245,
+  "<action_498>": 152246,
+  "<action_499>": 152247,
+  "<action_49>": 151797,
+  "<action_4>": 151752,
+  "<action_500>": 152248,
+  "<action_501>": 152249,
+  "<action_502>": 152250,
+  "<action_503>": 152251,
+  "<action_504>": 152252,
+  "<action_505>": 152253,
+  "<action_506>": 152254,
+  "<action_507>": 152255,
+  "<action_508>": 152256,
+  "<action_509>": 152257,
+  "<action_50>": 151798,
+  "<action_510>": 152258,
+  "<action_511>": 152259,
+  "<action_512>": 152260,
+  "<action_513>": 152261,
+  "<action_514>": 152262,
+  "<action_515>": 152263,
+  "<action_516>": 152264,
+  "<action_517>": 152265,
+  "<action_518>": 152266,
+  "<action_519>": 152267,
+  "<action_51>": 151799,
+  "<action_520>": 152268,
+  "<action_521>": 152269,
+  "<action_522>": 152270,
+  "<action_523>": 152271,
+  "<action_524>": 152272,
+  "<action_525>": 152273,
+  "<action_526>": 152274,
+  "<action_527>": 152275,
+  "<action_528>": 152276,
+  "<action_529>": 152277,
+  "<action_52>": 151800,
+  "<action_530>": 152278,
+  "<action_531>": 152279,
+  "<action_532>": 152280,
+  "<action_533>": 152281,
+  "<action_534>": 152282,
+  "<action_535>": 152283,
+  "<action_536>": 152284,
+  "<action_537>": 152285,
+  "<action_538>": 152286,
+  "<action_539>": 152287,
+  "<action_53>": 151801,
+  "<action_540>": 152288,
+  "<action_541>": 152289,
+  "<action_542>": 152290,
+  "<action_543>": 152291,
+  "<action_544>": 152292,
+  "<action_545>": 152293,
+  "<action_546>": 152294,
+  "<action_547>": 152295,
+  "<action_548>": 152296,
+  "<action_549>": 152297,
+  "<action_54>": 151802,
+  "<action_550>": 152298,
+  "<action_551>": 152299,
+  "<action_552>": 152300,
+  "<action_553>": 152301,
+  "<action_554>": 152302,
+  "<action_555>": 152303,
+  "<action_556>": 152304,
+  "<action_557>": 152305,
+  "<action_558>": 152306,
+  "<action_559>": 152307,
+  "<action_55>": 151803,
+  "<action_560>": 152308,
+  "<action_561>": 152309,
+  "<action_562>": 152310,
+  "<action_563>": 152311,
+  "<action_564>": 152312,
+  "<action_565>": 152313,
+  "<action_566>": 152314,
+  "<action_567>": 152315,
+  "<action_568>": 152316,
+  "<action_569>": 152317,
+  "<action_56>": 151804,
+  "<action_570>": 152318,
+  "<action_571>": 152319,
+  "<action_572>": 152320,
+  "<action_573>": 152321,
+  "<action_574>": 152322,
+  "<action_575>": 152323,
+  "<action_576>": 152324,
+  "<action_577>": 152325,
+  "<action_578>": 152326,
+  "<action_579>": 152327,
+  "<action_57>": 151805,
+  "<action_580>": 152328,
+  "<action_581>": 152329,
+  "<action_582>": 152330,
+  "<action_583>": 152331,
+  "<action_584>": 152332,
+  "<action_585>": 152333,
+  "<action_586>": 152334,
+  "<action_587>": 152335,
+  "<action_588>": 152336,
+  "<action_589>": 152337,
+  "<action_58>": 151806,
+  "<action_590>": 152338,
+  "<action_591>": 152339,
+  "<action_592>": 152340,
+  "<action_593>": 152341,
+  "<action_594>": 152342,
+  "<action_595>": 152343,
+  "<action_596>": 152344,
+  "<action_597>": 152345,
+  "<action_598>": 152346,
+  "<action_599>": 152347,
+  "<action_59>": 151807,
+  "<action_5>": 151753,
+  "<action_600>": 152348,
+  "<action_601>": 152349,
+  "<action_602>": 152350,
+  "<action_603>": 152351,
+  "<action_604>": 152352,
+  "<action_605>": 152353,
+  "<action_606>": 152354,
+  "<action_607>": 152355,
+  "<action_608>": 152356,
+  "<action_609>": 152357,
+  "<action_60>": 151808,
+  "<action_610>": 152358,
+  "<action_611>": 152359,
+  "<action_612>": 152360,
+  "<action_613>": 152361,
+  "<action_614>": 152362,
+  "<action_615>": 152363,
+  "<action_616>": 152364,
+  "<action_617>": 152365,
+  "<action_618>": 152366,
+  "<action_619>": 152367,
+  "<action_61>": 151809,
+  "<action_620>": 152368,
+  "<action_621>": 152369,
+  "<action_622>": 152370,
+  "<action_623>": 152371,
+  "<action_624>": 152372,
+  "<action_625>": 152373,
+  "<action_626>": 152374,
+  "<action_627>": 152375,
+  "<action_628>": 152376,
+  "<action_629>": 152377,
+  "<action_62>": 151810,
+  "<action_630>": 152378,
+  "<action_631>": 152379,
+  "<action_632>": 152380,
+  "<action_633>": 152381,
+  "<action_634>": 152382,
+  "<action_635>": 152383,
+  "<action_636>": 152384,
+  "<action_637>": 152385,
+  "<action_638>": 152386,
+  "<action_639>": 152387,
+  "<action_63>": 151811,
+  "<action_640>": 152388,
+  "<action_641>": 152389,
+  "<action_642>": 152390,
+  "<action_643>": 152391,
+  "<action_644>": 152392,
+  "<action_645>": 152393,
+  "<action_646>": 152394,
+  "<action_647>": 152395,
+  "<action_648>": 152396,
+  "<action_649>": 152397,
+  "<action_64>": 151812,
+  "<action_650>": 152398,
+  "<action_651>": 152399,
+  "<action_652>": 152400,
+  "<action_653>": 152401,
+  "<action_654>": 152402,
+  "<action_655>": 152403,
+  "<action_656>": 152404,
+  "<action_657>": 152405,
+  "<action_658>": 152406,
+  "<action_659>": 152407,
+  "<action_65>": 151813,
+  "<action_660>": 152408,
+  "<action_661>": 152409,
+  "<action_662>": 152410,
+  "<action_663>": 152411,
+  "<action_664>": 152412,
+  "<action_665>": 152413,
+  "<action_666>": 152414,
+  "<action_667>": 152415,
+  "<action_668>": 152416,
+  "<action_669>": 152417,
+  "<action_66>": 151814,
+  "<action_670>": 152418,
+  "<action_671>": 152419,
+  "<action_672>": 152420,
+  "<action_673>": 152421,
+  "<action_674>": 152422,
+  "<action_675>": 152423,
+  "<action_676>": 152424,
+  "<action_677>": 152425,
+  "<action_678>": 152426,
+  "<action_679>": 152427,
+  "<action_67>": 151815,
+  "<action_680>": 152428,
+  "<action_681>": 152429,
+  "<action_682>": 152430,
+  "<action_683>": 152431,
+  "<action_684>": 152432,
+  "<action_685>": 152433,
+  "<action_686>": 152434,
+  "<action_687>": 152435,
+  "<action_688>": 152436,
+  "<action_689>": 152437,
+  "<action_68>": 151816,
+  "<action_690>": 152438,
+  "<action_691>": 152439,
+  "<action_692>": 152440,
+  "<action_693>": 152441,
+  "<action_694>": 152442,
+  "<action_695>": 152443,
+  "<action_696>": 152444,
+  "<action_697>": 152445,
+  "<action_698>": 152446,
+  "<action_699>": 152447,
+  "<action_69>": 151817,
+  "<action_6>": 151754,
+  "<action_700>": 152448,
+  "<action_701>": 152449,
+  "<action_702>": 152450,
+  "<action_703>": 152451,
+  "<action_704>": 152452,
+  "<action_705>": 152453,
+  "<action_706>": 152454,
+  "<action_707>": 152455,
+  "<action_708>": 152456,
+  "<action_709>": 152457,
+  "<action_70>": 151818,
+  "<action_710>": 152458,
+  "<action_711>": 152459,
+  "<action_712>": 152460,
+  "<action_713>": 152461,
+  "<action_714>": 152462,
+  "<action_715>": 152463,
+  "<action_716>": 152464,
+  "<action_717>": 152465,
+  "<action_718>": 152466,
+  "<action_719>": 152467,
+  "<action_71>": 151819,
+  "<action_720>": 152468,
+  "<action_721>": 152469,
+  "<action_722>": 152470,
+  "<action_723>": 152471,
+  "<action_724>": 152472,
+  "<action_725>": 152473,
+  "<action_726>": 152474,
+  "<action_727>": 152475,
+  "<action_728>": 152476,
+  "<action_729>": 152477,
+  "<action_72>": 151820,
+  "<action_730>": 152478,
+  "<action_731>": 152479,
+  "<action_732>": 152480,
+  "<action_733>": 152481,
+  "<action_734>": 152482,
+  "<action_735>": 152483,
+  "<action_736>": 152484,
+  "<action_737>": 152485,
+  "<action_738>": 152486,
+  "<action_739>": 152487,
+  "<action_73>": 151821,
+  "<action_740>": 152488,
+  "<action_741>": 152489,
+  "<action_742>": 152490,
+  "<action_743>": 152491,
+  "<action_744>": 152492,
+  "<action_745>": 152493,
+  "<action_746>": 152494,
+  "<action_747>": 152495,
+  "<action_748>": 152496,
+  "<action_749>": 152497,
+  "<action_74>": 151822,
+  "<action_750>": 152498,
+  "<action_751>": 152499,
+  "<action_752>": 152500,
+  "<action_753>": 152501,
+  "<action_754>": 152502,
+  "<action_755>": 152503,
+  "<action_756>": 152504,
+  "<action_757>": 152505,
+  "<action_758>": 152506,
+  "<action_759>": 152507,
+  "<action_75>": 151823,
+  "<action_760>": 152508,
+  "<action_761>": 152509,
+  "<action_762>": 152510,
+  "<action_763>": 152511,
+  "<action_764>": 152512,
+  "<action_765>": 152513,
+  "<action_766>": 152514,
+  "<action_767>": 152515,
+  "<action_768>": 152516,
+  "<action_769>": 152517,
+  "<action_76>": 151824,
+  "<action_770>": 152518,
+  "<action_771>": 152519,
+  "<action_772>": 152520,
+  "<action_773>": 152521,
+  "<action_774>": 152522,
+  "<action_775>": 152523,
+  "<action_776>": 152524,
+  "<action_777>": 152525,
+  "<action_778>": 152526,
+  "<action_779>": 152527,
+  "<action_77>": 151825,
+  "<action_780>": 152528,
+  "<action_781>": 152529,
+  "<action_782>": 152530,
+  "<action_783>": 152531,
+  "<action_784>": 152532,
+  "<action_785>": 152533,
+  "<action_786>": 152534,
+  "<action_787>": 152535,
+  "<action_788>": 152536,
+  "<action_789>": 152537,
+  "<action_78>": 151826,
+  "<action_790>": 152538,
+  "<action_791>": 152539,
+  "<action_792>": 152540,
+  "<action_793>": 152541,
+  "<action_794>": 152542,
+  "<action_795>": 152543,
+  "<action_796>": 152544,
+  "<action_797>": 152545,
+  "<action_798>": 152546,
+  "<action_799>": 152547,
+  "<action_79>": 151827,
+  "<action_7>": 151755,
+  "<action_800>": 152548,
+  "<action_801>": 152549,
+  "<action_802>": 152550,
+  "<action_803>": 152551,
+  "<action_804>": 152552,
+  "<action_805>": 152553,
+  "<action_806>": 152554,
+  "<action_807>": 152555,
+  "<action_808>": 152556,
+  "<action_809>": 152557,
+  "<action_80>": 151828,
+  "<action_810>": 152558,
+  "<action_811>": 152559,
+  "<action_812>": 152560,
+  "<action_813>": 152561,
+  "<action_814>": 152562,
+  "<action_815>": 152563,
+  "<action_816>": 152564,
+  "<action_817>": 152565,
+  "<action_818>": 152566,
+  "<action_819>": 152567,
+  "<action_81>": 151829,
+  "<action_820>": 152568,
+  "<action_821>": 152569,
+  "<action_822>": 152570,
+  "<action_823>": 152571,
+  "<action_824>": 152572,
+  "<action_825>": 152573,
+  "<action_826>": 152574,
+  "<action_827>": 152575,
+  "<action_828>": 152576,
+  "<action_829>": 152577,
+  "<action_82>": 151830,
+  "<action_830>": 152578,
+  "<action_831>": 152579,
+  "<action_832>": 152580,
+  "<action_833>": 152581,
+  "<action_834>": 152582,
+  "<action_835>": 152583,
+  "<action_836>": 152584,
+  "<action_837>": 152585,
+  "<action_838>": 152586,
+  "<action_839>": 152587,
+  "<action_83>": 151831,
+  "<action_840>": 152588,
+  "<action_841>": 152589,
+  "<action_842>": 152590,
+  "<action_843>": 152591,
+  "<action_844>": 152592,
+  "<action_845>": 152593,
+  "<action_846>": 152594,
+  "<action_847>": 152595,
+  "<action_848>": 152596,
+  "<action_849>": 152597,
+  "<action_84>": 151832,
+  "<action_850>": 152598,
+  "<action_851>": 152599,
+  "<action_852>": 152600,
+  "<action_853>": 152601,
+  "<action_854>": 152602,
+  "<action_855>": 152603,
+  "<action_856>": 152604,
+  "<action_857>": 152605,
+  "<action_858>": 152606,
+  "<action_859>": 152607,
+  "<action_85>": 151833,
+  "<action_860>": 152608,
+  "<action_861>": 152609,
+  "<action_862>": 152610,
+  "<action_863>": 152611,
+  "<action_864>": 152612,
+  "<action_865>": 152613,
+  "<action_866>": 152614,
+  "<action_867>": 152615,
+  "<action_868>": 152616,
+  "<action_869>": 152617,
+  "<action_86>": 151834,
+  "<action_870>": 152618,
+  "<action_871>": 152619,
+  "<action_872>": 152620,
+  "<action_873>": 152621,
+  "<action_874>": 152622,
+  "<action_875>": 152623,
+  "<action_876>": 152624,
+  "<action_877>": 152625,
+  "<action_878>": 152626,
+  "<action_879>": 152627,
+  "<action_87>": 151835,
+  "<action_880>": 152628,
+  "<action_881>": 152629,
+  "<action_882>": 152630,
+  "<action_883>": 152631,
+  "<action_884>": 152632,
+  "<action_885>": 152633,
+  "<action_886>": 152634,
+  "<action_887>": 152635,
+  "<action_888>": 152636,
+  "<action_889>": 152637,
+  "<action_88>": 151836,
+  "<action_890>": 152638,
+  "<action_891>": 152639,
+  "<action_892>": 152640,
+  "<action_893>": 152641,
+  "<action_894>": 152642,
+  "<action_895>": 152643,
+  "<action_896>": 152644,
+  "<action_897>": 152645,
+  "<action_898>": 152646,
+  "<action_899>": 152647,
+  "<action_89>": 151837,
+  "<action_8>": 151756,
+  "<action_900>": 152648,
+  "<action_901>": 152649,
+  "<action_902>": 152650,
+  "<action_903>": 152651,
+  "<action_904>": 152652,
+  "<action_905>": 152653,
+  "<action_906>": 152654,
+  "<action_907>": 152655,
+  "<action_908>": 152656,
+  "<action_909>": 152657,
+  "<action_90>": 151838,
+  "<action_910>": 152658,
+  "<action_911>": 152659,
+  "<action_912>": 152660,
+  "<action_913>": 152661,
+  "<action_914>": 152662,
+  "<action_915>": 152663,
+  "<action_916>": 152664,
+  "<action_917>": 152665,
+  "<action_918>": 152666,
+  "<action_919>": 152667,
+  "<action_91>": 151839,
+  "<action_920>": 152668,
+  "<action_921>": 152669,
+  "<action_922>": 152670,
+  "<action_923>": 152671,
+  "<action_924>": 152672,
+  "<action_925>": 152673,
+  "<action_926>": 152674,
+  "<action_927>": 152675,
+  "<action_928>": 152676,
+  "<action_929>": 152677,
+  "<action_92>": 151840,
+  "<action_930>": 152678,
+  "<action_931>": 152679,
+  "<action_932>": 152680,
+  "<action_933>": 152681,
+  "<action_934>": 152682,
+  "<action_935>": 152683,
+  "<action_936>": 152684,
+  "<action_937>": 152685,
+  "<action_938>": 152686,
+  "<action_939>": 152687,
+  "<action_93>": 151841,
+  "<action_940>": 152688,
+  "<action_941>": 152689,
+  "<action_942>": 152690,
+  "<action_943>": 152691,
+  "<action_944>": 152692,
+  "<action_945>": 152693,
+  "<action_946>": 152694,
+  "<action_947>": 152695,
+  "<action_948>": 152696,
+  "<action_949>": 152697,
+  "<action_94>": 151842,
+  "<action_950>": 152698,
+  "<action_951>": 152699,
+  "<action_952>": 152700,
+  "<action_953>": 152701,
+  "<action_954>": 152702,
+  "<action_955>": 152703,
+  "<action_956>": 152704,
+  "<action_957>": 152705,
+  "<action_958>": 152706,
+  "<action_959>": 152707,
+  "<action_95>": 151843,
+  "<action_960>": 152708,
+  "<action_961>": 152709,
+  "<action_962>": 152710,
+  "<action_963>": 152711,
+  "<action_964>": 152712,
+  "<action_965>": 152713,
+  "<action_966>": 152714,
+  "<action_967>": 152715,
+  "<action_968>": 152716,
+  "<action_969>": 152717,
+  "<action_96>": 151844,
+  "<action_970>": 152718,
+  "<action_971>": 152719,
+  "<action_972>": 152720,
+  "<action_973>": 152721,
+  "<action_974>": 152722,
+  "<action_975>": 152723,
+  "<action_976>": 152724,
+  "<action_977>": 152725,
+  "<action_978>": 152726,
+  "<action_979>": 152727,
+  "<action_97>": 151845,
+  "<action_980>": 152728,
+  "<action_981>": 152729,
+  "<action_982>": 152730,
+  "<action_983>": 152731,
+  "<action_984>": 152732,
+  "<action_985>": 152733,
+  "<action_986>": 152734,
+  "<action_987>": 152735,
+  "<action_988>": 152736,
+  "<action_989>": 152737,
+  "<action_98>": 151846,
+  "<action_990>": 152738,
+  "<action_991>": 152739,
+  "<action_992>": 152740,
+  "<action_993>": 152741,
+  "<action_994>": 152742,
+  "<action_995>": 152743,
+  "<action_996>": 152744,
+  "<action_997>": 152745,
+  "<action_998>": 152746,
+  "<action_999>": 152747,
+  "<action_99>": 151847,
+  "<action_9>": 151757,
+  "<box>": 151673,
+  "<image>": 151669,
+  "<image_id>": 151681,
+  "<point>": 151677,
+  "<quad>": 151675,
+  "<ref>": 151671,
+  "<slice>": 151679,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<unit>": 151683,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|reserved_0|>": 151685,
+  "<|reserved_10|>": 151695,
+  "<|reserved_11|>": 151696,
+  "<|reserved_12|>": 151697,
+  "<|reserved_13|>": 151698,
+  "<|reserved_14|>": 151699,
+  "<|reserved_15|>": 151700,
+  "<|reserved_16|>": 151701,
+  "<|reserved_17|>": 151702,
+  "<|reserved_18|>": 151703,
+  "<|reserved_19|>": 151704,
+  "<|reserved_1|>": 151686,
+  "<|reserved_20|>": 151705,
+  "<|reserved_21|>": 151706,
+  "<|reserved_22|>": 151707,
+  "<|reserved_23|>": 151708,
+  "<|reserved_24|>": 151709,
+  "<|reserved_25|>": 151710,
+  "<|reserved_26|>": 151711,
+  "<|reserved_27|>": 151712,
+  "<|reserved_28|>": 151713,
+  "<|reserved_29|>": 151714,
+  "<|reserved_2|>": 151687,
+  "<|reserved_30|>": 151715,
+  "<|reserved_31|>": 151716,
+  "<|reserved_32|>": 151717,
+  "<|reserved_33|>": 151718,
+  "<|reserved_34|>": 151719,
+  "<|reserved_35|>": 151720,
+  "<|reserved_36|>": 151721,
+  "<|reserved_37|>": 151722,
+  "<|reserved_38|>": 151723,
+  "<|reserved_39|>": 151724,
+  "<|reserved_3|>": 151688,
+  "<|reserved_40|>": 151725,
+  "<|reserved_41|>": 151726,
+  "<|reserved_42|>": 151727,
+  "<|reserved_43|>": 151728,
+  "<|reserved_44|>": 151729,
+  "<|reserved_45|>": 151730,
+  "<|reserved_46|>": 151731,
+  "<|reserved_47|>": 151732,
+  "<|reserved_48|>": 151733,
+  "<|reserved_49|>": 151734,
+  "<|reserved_4|>": 151689,
+  "<|reserved_50|>": 151735,
+  "<|reserved_51|>": 151736,
+  "<|reserved_52|>": 151737,
+  "<|reserved_53|>": 151738,
+  "<|reserved_54|>": 151739,
+  "<|reserved_55|>": 151740,
+  "<|reserved_56|>": 151741,
+  "<|reserved_57|>": 151742,
+  "<|reserved_58|>": 151743,
+  "<|reserved_59|>": 151744,
+  "<|reserved_5|>": 151690,
+  "<|reserved_60|>": 151745,
+  "<|reserved_61|>": 151746,
+  "<|reserved_62|>": 151747,
+  "<|reserved_6|>": 151691,
+  "<|reserved_7|>": 151692,
+  "<|reserved_8|>": 151693,
+  "<|reserved_9|>": 151694,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

config.json ADDED Viewed

	@@ -0,0 +1,60 @@

+{
+  "architectures": [
+    "MiniCPMV"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "batch_3d_resampler": true,
+  "batch_vision_input": true,
+  "bos_token_id": 151643,
+  "drop_vision_last_layer": false,
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "image_size": 448,
+  "initializer_range": 0.02,
+  "intermediate_size": 12288,
+  "max_position_embeddings": 40960,
+  "max_window_layers": 36,
+  "model_type": "minicpmv",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "patch_size": 14,
+  "query_num": 64,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "slice_config": {
+    "max_slice_nums": 9,
+    "model_type": "minicpmv",
+    "patch_size": 14,
+    "scale_resolution": 448
+  },
+  "slice_mode": true,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.2",
+  "use_cache": true,
+  "use_image_id": true,
+  "use_sliding_window": false,
+  "version": 4.5,
+  "vision_batch_size": 16,
+  "vision_config": {
+    "_attn_implementation_autoset": true,
+    "attention_dropout": 0.0,
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "image_size": 980,
+    "intermediate_size": 4304,
+    "layer_norm_eps": 1e-06,
+    "model_type": "siglip_vision_model",
+    "num_attention_heads": 16,
+    "num_channels": 3,
+    "num_hidden_layers": 27,
+    "patch_size": 14
+  },
+  "vocab_size": 153796
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,16 @@

+{
+  "bos_token_id": 151643,
+  "chat_template_kwargs": {
+    "enable_thinking": false
+  },
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "4.51.2"
+}

image_processing_minicpmv.py ADDED Viewed

	@@ -0,0 +1,501 @@

+from typing import Optional, Union, Dict, Any, List
+from itertools import chain
+import torch
+import math
+import PIL.Image
+import PIL.ImageSequence
+import numpy as np
+import PIL
+from PIL import Image
+from transformers.utils import TensorType, requires_backends, is_torch_dtype, is_torch_device
+from transformers.image_processing_utils import BaseImageProcessor, BatchFeature
+from transformers import AutoImageProcessor
+from transformers.image_transforms import to_channel_dimension_format
+from transformers.image_utils import (
+    ImageInput,
+    make_list_of_images,
+    valid_images,
+    is_torch_tensor,
+    is_batched,
+    to_numpy_array,
+    infer_channel_dimension_format,
+    ChannelDimension
+)
+def recursive_converter(converter, value):
+    if isinstance(value, list):
+        new_value = []
+        for v in value:
+            new_value += [recursive_converter(converter, v)]
+        return new_value
+    else:
+        return converter(value)
+def list_depth(lst):
+    if not isinstance(lst, list) and not isinstance(lst, np.ndarray):
+        return 0
+    # if not lst:  # 空列表
+    #     return 1
+    return 1 + max(list_depth(item) for item in lst)
+class MiniCPMVBatchFeature(BatchFeature):
+    r"""
+    Extend from BatchFeature for supporting various image size
+    """
+    def __init__(self, data: Optional[Dict[str, Any]] = None, tensor_type: Union[None, str, TensorType] = None):
+        super().__init__(data)
+        self.convert_to_tensors(tensor_type=tensor_type)
+    def convert_to_tensors(self, tensor_type: Optional[Union[str, TensorType]] = None):
+        if tensor_type is None:
+            return self
+        is_tensor, as_tensor = self._get_is_as_tensor_fns(tensor_type)
+        def converter(value):
+            try:
+                if not is_tensor(value):
+                    tensor = as_tensor(value)
+                    return tensor
+            except:  # noqa E722
+                if key == "overflowing_values":
+                    raise ValueError("Unable to create tensor returning overflowing values of different lengths. ")
+                raise ValueError(
+                    "Unable to create tensor, you should probably activate padding "
+                    "with 'padding=True' to have batched tensors with the same length."
+                )
+        for key, value in self.items():
+            self[key] = recursive_converter(converter, value)
+        return self
+    def to(self, *args, **kwargs) -> "MiniCPMVBatchFeature":
+        requires_backends(self, ["torch"])
+        import torch
+        def cast_tensor(v):
+            # check if v is a floating point
+            if torch.is_floating_point(v):
+                # cast and send to device
+                return v.to(*args, **kwargs)
+            elif device is not None:
+                return v.to(device=device)
+            else:
+                return v
+        new_data = {}
+        device = kwargs.get("device")
+        # Check if the args are a device or a dtype
+        if device is None and len(args) > 0:
+            # device should be always the first argument
+            arg = args[0]
+            if is_torch_dtype(arg):
+                # The first argument is a dtype
+                pass
+            elif isinstance(arg, str) or is_torch_device(arg) or isinstance(arg, int):
+                device = arg
+            else:
+                # it's something else
+                raise ValueError(f"Attempting to cast a BatchFeature to type {str(arg)}. This is not supported.")
+        # We cast only floating point tensors to avoid issues with tokenizers casting `LongTensor` to `FloatTensor`
+        for k, v in self.items():
+            new_data[k] = recursive_converter(cast_tensor, v)
+        self.data = new_data
+        return self
+class MiniCPMVImageProcessor(BaseImageProcessor):
+    model_input_names = ["pixel_values"]
+    def __init__(
+            self,
+            max_slice_nums=9,
+            scale_resolution=448,
+            patch_size=14,
+            **kwargs):
+        super().__init__(**kwargs)
+        self.max_slice_nums = max_slice_nums
+        self.scale_resolution = scale_resolution
+        self.patch_size = patch_size
+        self.use_image_id = kwargs.pop("use_image_id", False)
+        self.image_feature_size = kwargs.pop("image_feature_size", 64)
+        self.im_start_token = kwargs.pop("im_start", "<image>")
+        self.im_end_token = kwargs.pop("im_end", "</image>")
+        self.slice_start_token = kwargs.pop("slice_start", "<slice>")
+        self.slice_end_token = kwargs.pop("slice_end", "</slice>")
+        self.unk_token = kwargs.pop("unk", "<unk>")
+        self.im_id_start = kwargs.pop("im_id_start", "<image_id>")
+        self.im_id_end = kwargs.pop("im_id_end", "</image_id>")
+        self.slice_mode = kwargs.pop("slice_mode", True)
+        self.mean = np.array(kwargs.pop("norm_mean", [0.5, 0.5, 0.5]))
+        self.std = np.array(kwargs.pop("norm_std", [0.5, 0.5, 0.5]))
+        self.version = kwargs.pop("version", 2.0)
+    def ensure_divide(self, length, patch_size):
+        return max(round(length / patch_size) * patch_size, patch_size)
+    def find_best_resize(self,
+                         original_size,
+                         scale_resolution,
+                         patch_size,
+                         allow_upscale=False):
+        width, height = original_size
+        if (width * height >
+                scale_resolution * scale_resolution) or allow_upscale:
+            r = width / height
+            height = int(scale_resolution / math.sqrt(r))
+            width = int(height * r)
+        best_width = self.ensure_divide(width, patch_size)
+        best_height = self.ensure_divide(height, patch_size)
+        return (best_width, best_height)
+    def get_refine_size(self,
+                        original_size,
+                        grid,
+                        scale_resolution,
+                        patch_size,
+                        allow_upscale=False):
+        width, height = original_size
+        grid_x, grid_y = grid
+        refine_width = self.ensure_divide(width, grid_x)
+        refine_height = self.ensure_divide(height, grid_y)
+        grid_width = refine_width / grid_x
+        grid_height = refine_height / grid_y
+        best_grid_size = self.find_best_resize((grid_width, grid_height),
+                                               scale_resolution,
+                                               patch_size,
+                                               allow_upscale=allow_upscale)
+        refine_size = (best_grid_size[0] * grid_x, best_grid_size[1] * grid_y)
+        return refine_size
+    def split_to_patches(self, image, grid):
+        patches = []
+        width, height = image.size
+        grid_x = int(width / grid[0])
+        grid_y = int(height / grid[1])
+        for i in range(0, height, grid_y):
+            images = []
+            for j in range(0, width, grid_x):
+                box = (j, i, j + grid_x, i + grid_y)
+                patch = image.crop(box)
+                images.append(patch)
+            patches.append(images)
+        return patches
+    def slice_image(
+        self, image, max_slice_nums=9, scale_resolution=448, patch_size=14, never_split=False
+    ):
+        original_size = image.size
+        source_image = None
+        best_grid = self.get_sliced_grid(original_size, max_slice_nums, never_split)
+        patches = []
+        if best_grid is None:
+            # dont need to slice, upsample
+            best_size = self.find_best_resize(
+                original_size, scale_resolution, patch_size, allow_upscale=True
+            )
+            source_image = image.resize(best_size, resample=Image.Resampling.BICUBIC)
+        else:
+            # source image, down-sampling and ensure divided by patch_size
+            best_resize = self.find_best_resize(original_size, scale_resolution, patch_size)
+            source_image = image.copy().resize(best_resize, resample=Image.Resampling.BICUBIC)
+            refine_size = self.get_refine_size(
+                original_size, best_grid, scale_resolution, patch_size, allow_upscale=True
+            )
+            refine_image = image.resize(refine_size, resample=Image.Resampling.BICUBIC)
+            patches = self.split_to_patches(refine_image, best_grid)
+        return source_image, patches, best_grid
+    def get_grid_placeholder(self, grid):
+        if grid is None:
+            return ""
+        slice_image_placeholder = (
+            self.slice_start_token
+            + self.unk_token * self.image_feature_size
+            + self.slice_end_token
+        )
+        cols = grid[0]
+        rows = grid[1]
+        slices = []
+        for i in range(rows):
+            lines = []
+            for j in range(cols):
+                lines.append(slice_image_placeholder)
+            slices.append("".join(lines))
+        slice_placeholder = "\n".join(slices)
+        return slice_placeholder
+    def get_image_id_placeholder(self, idx=0):
+        return f"{self.im_id_start}{idx}{self.im_id_end}"
+    def get_sliced_images(self, image, max_slice_nums=None):
+        slice_images = []
+        if not self.slice_mode:
+            return [image]
+        max_slice_nums = self.max_slice_nums if max_slice_nums is None else int(max_slice_nums)
+        assert max_slice_nums > 0
+        source_image, patches, sliced_grid = self.slice_image(
+            image,
+            max_slice_nums,  # default: 9
+            self.scale_resolution,  # default: 448
+            self.patch_size  # default: 14
+        )
+        slice_images.append(source_image)
+        if len(patches) > 0:
+            for i in range(len(patches)):
+                for j in range(len(patches[0])):
+                    slice_images.append(patches[i][j])
+        return slice_images
+    def get_sliced_grid(self, image_size, max_slice_nums, nerver_split=False):
+        original_width, original_height = image_size
+        log_ratio = math.log(original_width / original_height)
+        ratio = original_width * original_height / (self.scale_resolution * self.scale_resolution)
+        multiple = min(math.ceil(ratio), max_slice_nums)
+        if multiple <= 1 or nerver_split:
+            return None
+        candidate_split_grids_nums = []
+        for i in [multiple - 1, multiple, multiple + 1]:
+            if i == 1 or i > max_slice_nums:
+                continue
+            candidate_split_grids_nums.append(i)
+        candidate_grids = []
+        for split_grids_nums in candidate_split_grids_nums:
+            m = 1
+            while m <= split_grids_nums:
+                if split_grids_nums % m == 0:
+                    candidate_grids.append([m, split_grids_nums // m])
+                m += 1
+        best_grid = [1, 1]
+        min_error = float("inf")
+        for grid in candidate_grids:
+            error = abs(log_ratio - math.log(grid[0] / grid[1]))
+            if error < min_error:
+                best_grid = grid
+                min_error = error
+        return best_grid
+    def get_slice_image_placeholder(self, image_size, image_idx=0, max_slice_nums=None, use_image_id=None):
+        max_slice_nums = self.max_slice_nums if max_slice_nums is None else int(max_slice_nums)
+        assert max_slice_nums > 0
+        grid = self.get_sliced_grid(image_size=image_size, max_slice_nums=max_slice_nums)
+        image_placeholder = (
+            self.im_start_token
+            + self.unk_token * self.image_feature_size
+            + self.im_end_token
+        )
+        use_image_id = self.use_image_id if use_image_id is None else bool(use_image_id)
+        if use_image_id:
+            final_placeholder = self.get_image_id_placeholder(image_idx) + image_placeholder
+        else:
+            final_placeholder = image_placeholder
+        if self.slice_mode:
+            final_placeholder = final_placeholder + self.get_grid_placeholder(grid=grid)
+        return final_placeholder
+    def to_pil_image(self, image, rescale=None) -> PIL.Image.Image:
+        """
+        Converts `image` to a PIL Image. Optionally rescales it and puts the channel dimension back as the last axis if
+        needed.
+        Args:
+            image (`PIL.Image.Image` or `numpy.ndarray` or `torch.Tensor`):
+                The image to convert to the PIL Image format.
+            rescale (`bool`, *optional*):
+                Whether or not to apply the scaling factor (to make pixel values integers between 0 and 255). Will
+                default to `True` if the image type is a floating type, `False` otherwise.
+        """
+        if isinstance(image, PIL.Image.Image):
+            return image
+        if is_torch_tensor(image):
+            image = image.numpy()
+        if isinstance(image, np.ndarray):
+            if rescale is None:
+                # rescale default to the array being of floating type.
+                rescale = isinstance(image.flat[0], np.floating)
+            # If the channel as been moved to first dim, we put it back at the end.
+            if image.ndim == 3 and image.shape[0] in [1, 3]:
+                image = image.transpose(1, 2, 0)
+            if rescale:
+                image = image * 255
+            image = image.astype(np.uint8)
+            return PIL.Image.fromarray(image)
+        return image
+    def reshape_by_patch(self, image):
+        """
+        :param image: shape [3, H, W]
+        :param patch_size:
+        :return: [3, patch_size, HW/patch_size]
+        """
+        image = torch.from_numpy(image)
+        patch_size = self.patch_size
+        patches = torch.nn.functional.unfold(
+            image,
+            (patch_size, patch_size),
+            stride=(patch_size, patch_size)
+        )
+        patches = patches.reshape(image.size(0), patch_size, patch_size, -1)
+        patches = patches.permute(0, 1, 3, 2).reshape(image.size(0), patch_size, -1)
+        return patches.numpy()
+    def preprocess(
+            self,
+            images: Union[Image.Image, List[Image.Image], List[List[Image.Image]]],
+            do_pad: Optional[bool] = True, # TODO: add pad for MiniCPM-Llama3-V-2_5
+            max_slice_nums: int = None,
+            temporal_ids: Optional[Union[List[List[int]], List[List[List[int]]]]] = None,
+            return_tensors: Optional[Union[str, TensorType]] = None,
+            **kwargs
+        ) -> MiniCPMVBatchFeature:
+        if isinstance(images, Image.Image):
+            images_list = [[images]]
+        elif isinstance(images[0], Image.Image):
+            images_list = [images]
+        else:
+            images_list = images
+        if temporal_ids is not None:
+            if list_depth(temporal_ids) == 2:
+                temporal_ids = [temporal_ids]
+        new_images_list = []
+        image_sizes_list = []
+        tgt_sizes_list = []
+        temporal_ids_list = []
+        skip_image_idx_list = []
+        for batch_idx, _images in enumerate(images_list):
+            if _images is None or len(_images) == 0:
+                new_images_list.append([])
+                image_sizes_list.append([])
+                tgt_sizes_list.append([])
+                temporal_ids_list.append([])
+                skip_image_idx_list.append([])
+                continue
+            if not valid_images(_images):
+                raise ValueError(
+                    "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
+                    "torch.Tensor, tf.Tensor or jax.ndarray."
+                )
+            _images = [self.to_pil_image(image).convert("RGB") for image in _images]
+            input_data_format = infer_channel_dimension_format(np.array(_images[0]))
+            new_images = []
+            image_sizes = [image.size for image in _images]
+            tgt_sizes = []
+            tp_ids = []
+            skip_image_idx = []
+            # for image in _images:
+            #     image_patches = self.get_sliced_images(image, max_slice_nums)
+            #     image_patches = [to_numpy_array(image).astype(np.float32) / 255 for image in image_patches]
+            #     image_patches = [
+            #         self.normalize(image=image, mean=self.mean, std=self.std, input_data_format=input_data_format)
+            #             for image in image_patches
+            #     ]
+            #     image_patches = [
+            #         to_channel_dimension_format(image, ChannelDimension.FIRST, input_channel_dim=input_data_format)
+            #             for image in image_patches
+            #     ]
+            #     for slice_image in image_patches:
+            #         new_images.append(self.reshape_by_patch(slice_image))
+            #         tgt_sizes.append(np.array((slice_image.shape[1] // self.patch_size, slice_image.shape[2] // self.patch_size)))
+            if temporal_ids is None:
+                # no temporal ids
+                for image in _images:
+                    image_patches = self.get_sliced_images(image, max_slice_nums)
+                    image_patches = [to_numpy_array(image).astype(np.float32) / 255 for image in image_patches]
+                    image_patches = [
+                        self.normalize(image=image, mean=self.mean, std=self.std, input_data_format=input_data_format)
+                            for image in image_patches
+                    ]
+                    image_patches = [
+                        to_channel_dimension_format(image, ChannelDimension.FIRST, input_channel_dim=input_data_format)
+                            for image in image_patches
+                    ]
+                    for slice_image in image_patches:
+                        new_images.append(self.reshape_by_patch(slice_image))
+                        tgt_sizes.append(np.array((slice_image.shape[1] // self.patch_size, slice_image.shape[2] // self.patch_size)))
+                    tp_ids.extend([[-1]] * len(image_patches))
+            else:
+                temporal_ids_flatten = list(chain.from_iterable(temporal_ids[batch_idx]))
+                assert len(temporal_ids_flatten) == len(_images)
+                frame_groups = []
+                s = 0
+                for group in temporal_ids[batch_idx]:
+                    frame_groups.append(_images[s:s+len(group)])
+                    s += len(group)
+                skip_start = 0
+                for frame_group, tp_id in zip(frame_groups, temporal_ids[batch_idx]):
+                    image_patches_group = []
+                    for frame in frame_group:
+                        image_patches = self.get_sliced_images(frame, max_slice_nums)
+                        image_patches = [to_numpy_array(image).astype(np.float32) / 255 for image in image_patches]
+                        image_patches = [
+                            self.normalize(image=image, mean=self.mean, std=self.std, input_data_format=input_data_format)
+                                for image in image_patches
+                        ]
+                        image_patches = [
+                            to_channel_dimension_format(image, ChannelDimension.FIRST, input_channel_dim=input_data_format)
+                                for image in image_patches
+                        ]
+                        image_patches_group.append(image_patches)
+                    group_cnt = len(image_patches_group[0])
+                    for gidx in range(group_cnt):
+                        group_images = [s[gidx] for s in  image_patches_group]
+                        tgt_sizes.extend([np.array((i.shape[1] // self.patch_size, i.shape[2] // self.patch_size)) for i in group_images])
+                        group_images = [self.reshape_by_patch(i) for i in group_images]
+                        new_images.extend(group_images)
+                        tp_ids.append(tp_id)
+                    skip_image_idx.extend(list(range(skip_start + 1, skip_start + len(frame_group))))
+                    skip_start += len(frame_group)
+            if tgt_sizes:
+                tgt_sizes = np.vstack(tgt_sizes)
+            new_images_list.append(new_images)
+            image_sizes_list.append(image_sizes)
+            tgt_sizes_list.append(tgt_sizes)
+            temporal_ids_list.append(tp_ids)
+            skip_image_idx_list.append(skip_image_idx)
+        data = {
+            "pixel_values": new_images_list,
+            "image_sizes": image_sizes_list,
+            "tgt_sizes": tgt_sizes_list,
+            "temporal_ids": temporal_ids_list,
+            "skip_image_idx": skip_image_idx_list
+        }
+        return MiniCPMVBatchFeature(data=data, tensor_type=return_tensors)
+AutoImageProcessor.register("MiniCPMVImageProcessor", MiniCPMVImageProcessor)

merges.txt ADDED Viewed

The diff for this file is too large to render. See raw diff

model-00001-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:21daa5f10bcc95802543a9f4a5a01228cbaf636093c4b2621bc31b192d2a13a5
+size 4935818536

model-00002-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:d7c0ad33b64caa673b436ca24ea4354eebc518f29d39572827614d34e931c739
+size 4899159104

model-00003-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:933abd60e66bf5f2dd2705e23de7d1b5b8878698c99e5130892dd5d32be88f92
+size 4832048920

model-00004-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:6d4bb152f4202524fc2a6dac4643ea1c4c8fc34d4bdd186ad91770252d2af37f
+size 4999855832

model-00005-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:2a5bafd22096d007999e2b9a6ffdf4a90f5d2a713484921c63b3f44ecf0509ce
+size 4832048936

model-00006-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:9508dc11390edfa1dde9ad4883a7b71609b316f6555577454435185e57e53593
+size 4832048936

model-00007-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:443a88f69bab4e9cfce48952b4a5ba1e8f36232616fe2ec18b5145ab173d907d
+size 4997227096

model-00008-of-00008.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:7bb5dc4cdf0673de559548723e2683ae05fad88155eac993c69db64328eff681
+size 522581504

model.safetensors.index.json ADDED Viewed

	@@ -0,0 +1,856 @@

+{
+  "metadata": {
+    "total_size": 34850689984
+  },
+  "weight_map": {
+    "llm.lm_head.weight": "model-00007-of-00008.safetensors",
+    "llm.model.embed_tokens.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.input_layernorm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.mlp.down_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.mlp.gate_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.mlp.up_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.post_attention_layernorm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.self_attn.k_norm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.self_attn.k_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.self_attn.o_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.self_attn.q_norm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.self_attn.q_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.0.self_attn.v_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.input_layernorm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.mlp.down_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.mlp.gate_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.mlp.up_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.post_attention_layernorm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.self_attn.k_norm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.self_attn.k_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.self_attn.o_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.self_attn.q_norm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.self_attn.q_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.1.self_attn.v_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.10.input_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.mlp.down_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.mlp.gate_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.post_attention_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.self_attn.k_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.self_attn.k_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.self_attn.o_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.self_attn.q_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.self_attn.q_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.10.self_attn.v_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.input_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.mlp.down_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.mlp.gate_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.post_attention_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.self_attn.k_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.self_attn.k_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.self_attn.o_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.self_attn.q_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.self_attn.q_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.11.self_attn.v_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.input_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.mlp.down_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.mlp.gate_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.post_attention_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.self_attn.k_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.self_attn.k_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.self_attn.o_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.self_attn.q_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.self_attn.q_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.12.self_attn.v_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.input_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.mlp.down_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.mlp.gate_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.post_attention_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.self_attn.k_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.self_attn.k_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.self_attn.o_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.self_attn.q_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.self_attn.q_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.13.self_attn.v_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.input_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.mlp.down_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.mlp.gate_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.post_attention_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.self_attn.k_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.self_attn.k_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.self_attn.o_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.self_attn.q_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.self_attn.q_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.14.self_attn.v_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.15.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.15.mlp.gate_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.15.self_attn.k_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.self_attn.k_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.self_attn.o_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.self_attn.q_norm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.self_attn.q_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.15.self_attn.v_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.16.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.mlp.gate_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.mlp.up_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.16.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.mlp.gate_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.mlp.up_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.17.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.mlp.gate_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.mlp.up_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.18.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.mlp.gate_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.mlp.up_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.19.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.2.input_layernorm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.mlp.down_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.mlp.gate_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.mlp.up_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.post_attention_layernorm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.self_attn.k_norm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.self_attn.k_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.self_attn.o_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.self_attn.q_norm.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.self_attn.q_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.2.self_attn.v_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.20.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.mlp.gate_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.mlp.up_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.20.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.input_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.mlp.down_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.mlp.gate_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.mlp.up_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.post_attention_layernorm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.21.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.22.input_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.22.mlp.down_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.22.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.22.mlp.up_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.22.post_attention_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.22.self_attn.k_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.22.self_attn.k_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.22.self_attn.o_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.22.self_attn.q_norm.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.22.self_attn.q_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.22.self_attn.v_proj.weight": "model-00004-of-00008.safetensors",
+    "llm.model.layers.23.input_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.mlp.down_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.mlp.up_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.post_attention_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.self_attn.k_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.self_attn.k_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.self_attn.o_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.self_attn.q_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.self_attn.q_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.23.self_attn.v_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.input_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.mlp.down_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.mlp.up_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.post_attention_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.self_attn.k_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.self_attn.k_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.self_attn.o_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.self_attn.q_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.self_attn.q_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.24.self_attn.v_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.input_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.mlp.down_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.mlp.up_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.post_attention_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.self_attn.k_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.self_attn.k_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.self_attn.o_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.self_attn.q_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.self_attn.q_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.25.self_attn.v_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.input_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.mlp.down_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.mlp.up_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.post_attention_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.self_attn.k_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.self_attn.k_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.self_attn.o_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.self_attn.q_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.self_attn.q_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.26.self_attn.v_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.input_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.mlp.down_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.mlp.up_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.post_attention_layernorm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.self_attn.k_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.self_attn.k_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.self_attn.o_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.self_attn.q_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.self_attn.q_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.27.self_attn.v_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.input_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.28.mlp.down_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.28.mlp.gate_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.28.post_attention_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.28.self_attn.k_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.self_attn.k_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.self_attn.o_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.self_attn.q_norm.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.self_attn.q_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.28.self_attn.v_proj.weight": "model-00005-of-00008.safetensors",
+    "llm.model.layers.29.input_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.mlp.down_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.mlp.gate_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.post_attention_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.self_attn.k_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.self_attn.k_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.self_attn.o_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.self_attn.q_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.self_attn.q_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.29.self_attn.v_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.3.input_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.mlp.down_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.mlp.up_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.post_attention_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.self_attn.k_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.3.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.3.self_attn.q_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.3.self_attn.v_proj.weight": "model-00001-of-00008.safetensors",
+    "llm.model.layers.30.input_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.mlp.down_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.mlp.gate_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.post_attention_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.self_attn.k_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.self_attn.k_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.self_attn.o_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.self_attn.q_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.self_attn.q_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.30.self_attn.v_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.input_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.mlp.down_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.mlp.gate_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.post_attention_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.self_attn.k_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.self_attn.k_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.self_attn.o_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.self_attn.q_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.self_attn.q_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.31.self_attn.v_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.input_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.mlp.down_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.mlp.gate_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.post_attention_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.self_attn.k_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.self_attn.k_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.self_attn.o_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.self_attn.q_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.self_attn.q_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.32.self_attn.v_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.input_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.mlp.down_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.mlp.gate_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.post_attention_layernorm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.self_attn.k_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.self_attn.k_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.self_attn.o_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.self_attn.q_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.self_attn.q_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.33.self_attn.v_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.input_layernorm.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.34.mlp.down_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.34.mlp.gate_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.mlp.up_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.post_attention_layernorm.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.34.self_attn.k_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.self_attn.k_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.self_attn.o_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.self_attn.q_norm.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.self_attn.q_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.34.self_attn.v_proj.weight": "model-00006-of-00008.safetensors",
+    "llm.model.layers.35.input_layernorm.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.mlp.down_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.mlp.gate_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.mlp.up_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.post_attention_layernorm.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.self_attn.k_norm.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.self_attn.o_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.self_attn.q_norm.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.35.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "llm.model.layers.4.input_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.mlp.down_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.mlp.up_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.post_attention_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.self_attn.k_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.self_attn.q_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.4.self_attn.v_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.input_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.mlp.down_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.mlp.up_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.post_attention_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.self_attn.k_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.self_attn.q_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.5.self_attn.v_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.input_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.mlp.down_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.mlp.up_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.post_attention_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.self_attn.k_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.self_attn.q_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.6.self_attn.v_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.input_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.mlp.down_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.mlp.up_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.post_attention_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.self_attn.k_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.self_attn.q_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.7.self_attn.v_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.input_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.mlp.down_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.mlp.up_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.post_attention_layernorm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.self_attn.k_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.self_attn.q_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.8.self_attn.v_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.input_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.9.mlp.down_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.9.mlp.gate_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.mlp.up_proj.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.9.post_attention_layernorm.weight": "model-00003-of-00008.safetensors",
+    "llm.model.layers.9.self_attn.k_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.self_attn.k_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.self_attn.o_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.self_attn.q_norm.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.self_attn.q_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.layers.9.self_attn.v_proj.weight": "model-00002-of-00008.safetensors",
+    "llm.model.norm.weight": "model-00007-of-00008.safetensors",
+    "resampler.attn.in_proj_bias": "model-00008-of-00008.safetensors",
+    "resampler.attn.in_proj_weight": "model-00008-of-00008.safetensors",
+    "resampler.attn.out_proj.bias": "model-00008-of-00008.safetensors",
+    "resampler.attn.out_proj.weight": "model-00008-of-00008.safetensors",
+    "resampler.kv_proj.weight": "model-00008-of-00008.safetensors",
+    "resampler.ln_kv.bias": "model-00008-of-00008.safetensors",
+    "resampler.ln_kv.weight": "model-00008-of-00008.safetensors",
+    "resampler.ln_post.bias": "model-00008-of-00008.safetensors",
+    "resampler.ln_post.weight": "model-00008-of-00008.safetensors",
+    "resampler.ln_q.bias": "model-00008-of-00008.safetensors",
+    "resampler.ln_q.weight": "model-00008-of-00008.safetensors",
+    "resampler.proj": "model-00008-of-00008.safetensors",
+    "resampler.query": "model-00008-of-00008.safetensors",
+    "vpm.embeddings.patch_embedding.bias": "model-00007-of-00008.safetensors",
+    "vpm.embeddings.patch_embedding.weight": "model-00007-of-00008.safetensors",
+    "vpm.embeddings.position_embedding.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.0.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.1.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.10.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.11.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.12.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.13.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.14.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.15.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.16.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.17.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.18.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.19.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.2.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.20.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.21.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.22.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.23.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.24.layer_norm1.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.layer_norm1.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.layer_norm2.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.layer_norm2.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.mlp.fc1.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.mlp.fc1.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.mlp.fc2.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.mlp.fc2.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.out_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.out_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.24.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.25.layer_norm1.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.layer_norm1.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.layer_norm2.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.layer_norm2.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.mlp.fc1.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.mlp.fc1.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.mlp.fc2.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.mlp.fc2.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.k_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.k_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.out_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.out_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.q_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.q_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.v_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.25.self_attn.v_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.layer_norm1.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.layer_norm1.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.layer_norm2.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.layer_norm2.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.mlp.fc1.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.mlp.fc1.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.mlp.fc2.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.mlp.fc2.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.k_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.k_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.out_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.out_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.q_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.q_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.v_proj.bias": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.26.self_attn.v_proj.weight": "model-00008-of-00008.safetensors",
+    "vpm.encoder.layers.3.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.3.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.4.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.5.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.6.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.7.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.8.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.layer_norm1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.layer_norm1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.layer_norm2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.layer_norm2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.mlp.fc1.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.mlp.fc1.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.mlp.fc2.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.mlp.fc2.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.k_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.k_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.out_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.out_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.q_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.q_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.v_proj.bias": "model-00007-of-00008.safetensors",
+    "vpm.encoder.layers.9.self_attn.v_proj.weight": "model-00007-of-00008.safetensors",
+    "vpm.post_layernorm.bias": "model-00008-of-00008.safetensors",
+    "vpm.post_layernorm.weight": "model-00008-of-00008.safetensors"
+  }
+}

preprocessor_config.json ADDED Viewed

	@@ -0,0 +1,24 @@

+{
+    "image_processor_type": "MiniCPMVImageProcessor",
+    "auto_map": {
+        "AutoProcessor": "processing_minicpmv.MiniCPMVProcessor",
+        "AutoImageProcessor": "image_processing_minicpmv.MiniCPMVImageProcessor"
+      },
+    "processor_class": "MiniCPMVProcessor",
+    "max_slice_nums": 9,
+    "scale_resolution": 448,
+    "patch_size": 14,
+    "use_image_id": true,
+    "image_feature_size": 64,
+    "im_start": "<image>",
+    "im_end": "</image>",
+    "slice_start": "<slice>",
+    "slice_end": "</slice>",
+    "unk": "<unk>",
+    "im_id_start": "<image_id>",
+    "im_id_end": "</image_id>",
+    "slice_mode": true,
+    "norm_mean": [0.5, 0.5, 0.5],
+    "norm_std": [0.5, 0.5, 0.5],
+    "version": 2.6
+}

processing_minicpmv.py ADDED Viewed

	@@ -0,0 +1,255 @@

+# coding=utf-8
+# Copyright 2024 The HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Processor class for MiniCPMV.
+"""
+from typing import List, Optional, Union, Dict, Any
+import torch
+import re
+from transformers.image_processing_utils import BatchFeature
+from transformers.image_utils import ImageInput
+from transformers.processing_utils import ProcessorMixin
+from transformers.tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
+from transformers.utils import TensorType, requires_backends, is_torch_dtype, is_torch_device
+from .image_processing_minicpmv import MiniCPMVBatchFeature
+class MiniCPMVProcessor(ProcessorMixin):
+    r"""
+    Constructs a MiniCPMV processor which wraps a MiniCPMV image processor and a MiniCPMV tokenizer into a single processor.
+    [`MiniCPMVProcessor`] offers all the functionalities of [`MiniCPMVImageProcessor`] and [`LlamaTokenizerWrapper`]. See the
+    [`~MiniCPMVProcessor.__call__`] and [`~MiniCPMVProcessor.decode`] for more information.
+    Args:
+        image_processor ([`MiniCPMVImageProcessor`], *optional*):
+            The image processor is a required input.
+        tokenizer ([`LlamaTokenizerWrapper`], *optional*):
+            The tokenizer is a required input.
+    """
+    attributes = ["image_processor", "tokenizer"]
+    image_processor_class = "AutoImageProcessor"
+    tokenizer_class = "AutoTokenizer"
+    def __init__(self, image_processor=None, tokenizer=None):
+        super().__init__(image_processor, tokenizer)
+        self.version = image_processor.version
+    def __call__(
+        self,
+        text: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]],
+        images: ImageInput = None,
+        max_length: Optional[int] = None,
+        do_pad: Optional[bool] = True,
+        max_slice_nums: int = None,
+        use_image_id: bool = None,
+        temporal_ids: Optional[Union[List[List[int]], List[List[List[int]]]]] = None,
+        return_tensors: Optional[Union[str, TensorType]] = TensorType.PYTORCH,
+        **kwargs
+    ) -> MiniCPMVBatchFeature:
+        if images is not None:
+            # image_inputs = self.image_processor(images, do_pad=do_pad, max_slice_nums=max_slice_nums, return_tensors=return_tensors)
+            image_inputs = self.image_processor(images, do_pad=do_pad, max_slice_nums=max_slice_nums, temporal_ids=temporal_ids, return_tensors=return_tensors)
+        # return self._convert_images_texts_to_inputs(image_inputs, text, max_slice_nums=max_slice_nums, use_image_id=use_image_id, max_length=max_length, **kwargs)
+        return self._convert_images_texts_to_inputs(image_inputs, text, max_slice_nums=max_slice_nums, use_image_id=use_image_id, max_length=max_length, temporal_ids=temporal_ids, **kwargs)
+    # Copied from transformers.models.clip.processing_clip.CLIPProcessor.batch_decode with CLIP->Llama
+    def batch_decode(self, *args, **kwargs):
+        """
+        This method forwards all its arguments to LlamaTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please
+        refer to the docstring of this method for more information.
+        """
+        output_ids = args[0]
+        result_text = []
+        for result in output_ids:
+            result = result[result != 0]
+            if result[0] == self.tokenizer.bos_id:
+                result = result[1:]
+            if result[-1] == self.tokenizer.eos_id:
+                result = result[:-1]
+            result_text.append(self.tokenizer.decode(result, *args[1:], **kwargs).strip())
+        return result_text
+        # return self.tokenizer.batch_decode(*args, **kwargs)
+    # Copied from transformers.models.clip.processing_clip.CLIPProcessor.decode with CLIP->Llama
+    def decode(self, *args, **kwargs):
+        """
+        This method forwards all its arguments to LlamaTokenizerFast's [`~PreTrainedTokenizer.decode`]. Please refer to
+        the docstring of this method for more information.
+        """
+        result = args[0]
+        result = result[result != 0]
+        if result[0] == self.tokenizer.bos_id:
+            result = result[1:]
+        if result[-1] == self.tokenizer.eos_id or (hasattr(self.tokenizer, "eot_id") and result[-1] == self.tokenizer.eot_id):
+            result = result[:-1]
+        return self.tokenizer.decode(result, *args[1:], **kwargs).strip()
+    def _convert(
+        self, input_str, max_inp_length: Optional[int] = None
+    ):
+        if self.version > 2.5 or not getattr(self.tokenizer, "add_bos_token", False):
+            input_ids = self.tokenizer.encode(input_str)
+        else:
+            input_ids = [self.tokenizer.bos_id] + self.tokenizer.encode(input_str)
+        if max_inp_length is not None:
+            input_ids = input_ids[:max_inp_length]
+        input_ids = torch.tensor(input_ids, dtype=torch.int32)
+        start_cond = (input_ids == self.tokenizer.im_start_id) | (input_ids == self.tokenizer.slice_start_id)
+        end_cond = (input_ids == self.tokenizer.im_end_id) | (input_ids == self.tokenizer.slice_end_id)
+        image_start_tokens = torch.where(start_cond)[0]
+        image_start_tokens += 1
+        image_end_tokens = torch.where(end_cond)[0]
+        valid_image_nums = max(len(image_start_tokens), len(image_end_tokens))
+        image_bounds = torch.hstack(
+            [
+                image_start_tokens[:valid_image_nums].unsqueeze(-1),
+                image_end_tokens[:valid_image_nums].unsqueeze(-1),
+            ]
+        )
+        return input_ids, image_bounds
+    def _convert_images_texts_to_inputs(
+            self,
+            images,
+            texts: Union[str, List[str]],
+            truncation=None,
+            max_length=None,
+            max_slice_nums=None,
+            use_image_id=None,
+            return_tensors=None,
+            **kwargs
+        ):
+        if images is None or not len(images):
+            model_inputs = self.tokenizer(texts, return_tensors=return_tensors, truncation=truncation, max_length=max_length, **kwargs)
+            return MiniCPMVBatchFeature(data={**model_inputs})
+        pattern = "(<image>./</image>)"
+        # images, image_sizes, tgt_sizes = images["pixel_values"], images["image_sizes"], images["tgt_sizes"]
+        images, image_sizes, tgt_sizes, temporal_ids, skip_image_idx = images["pixel_values"], images["image_sizes"], images["tgt_sizes"], images["temporal_ids"], images["skip_image_idx"]
+        if isinstance(texts, str):
+            texts = [texts]
+        input_ids_list = []
+        image_bounds_list = []
+        for index, (text, skip_idx) in enumerate(zip(texts, skip_image_idx)):
+            image_tags = re.findall(pattern, text)
+            assert len(image_tags) == len(image_sizes[index])
+            text_chunks = text.split(pattern)
+            final_text = ""
+            for i in range(len(image_tags)):
+                if i in skip_idx:
+                    image_placeholder = ''
+                    text_chunk = text_chunks[i].strip()
+                else:
+                    image_placeholder = self.image_processor.get_slice_image_placeholder(
+                        image_sizes[index][i],
+                        i,
+                        max_slice_nums,
+                        use_image_id
+                    )
+                    text_chunk = text_chunks[i]
+                final_text = final_text + text_chunk + image_placeholder
+            final_text += text_chunks[-1]
+            input_ids, image_bounds = self._convert(final_text, max_length)
+            input_ids_list.append(input_ids)
+            image_bounds_list.append(image_bounds)
+        padded_input_ids, padding_lengths = self.pad(
+            input_ids_list,
+            padding_side="left"
+        )
+        for i, length in enumerate(padding_lengths):
+            image_bounds_list[i] = image_bounds_list[i] + length
+        attention_mask = padded_input_ids.ne(0)
+        return MiniCPMVBatchFeature(data={
+            "input_ids": padded_input_ids,
+            "attention_mask": attention_mask,
+            "pixel_values": images,
+            "image_sizes": image_sizes,
+            "image_bound": image_bounds_list,
+            "tgt_sizes": tgt_sizes,
+            "temporal_ids": temporal_ids
+        })
+    @property
+    # Copied from transformers.models.clip.processing_clip.CLIPProcessor.model_input_names
+    def model_input_names(self):
+        tokenizer_input_names = self.tokenizer.model_input_names
+        image_processor_input_names = self.image_processor.model_input_names
+        return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))
+    def pad(self, inputs, max_length=None, padding_value=0, padding_side="left"):
+        items = []
+        if isinstance(inputs[0], list):
+            assert isinstance(inputs[0][0], torch.Tensor)
+            for it in inputs:
+                for tr in it:
+                    items.append(tr)
+        else:
+            assert isinstance(inputs[0], torch.Tensor)
+            items = inputs
+        batch_size = len(items)
+        shape = items[0].shape
+        dim = len(shape)
+        assert dim <= 2
+        if max_length is None:
+            max_length = 0
+        max_length = max(max_length, max(item.shape[-1] for item in items))
+        min_length = min(item.shape[-1] for item in items)
+        dtype = items[0].dtype
+        if dim == 0:
+            return torch.stack([item for item in items], dim=0), [0]
+        elif dim == 1:
+            if max_length == min_length:
+                return torch.stack([item for item in items], dim=0), [0] * batch_size
+            tensor = torch.zeros((batch_size, max_length), dtype=dtype) + padding_value
+        else:
+            tensor = (
+                torch.zeros((batch_size, max_length, shape[-1]), dtype=dtype)
+                + padding_value
+            )
+        padding_length = []
+        for i, item in enumerate(items):
+            if dim == 1:
+                if padding_side == "left":
+                    tensor[i, -len(item) :] = item.clone()
+                else:
+                    tensor[i, : len(item)] = item.clone()
+            elif dim == 2:
+                if padding_side == "left":
+                    tensor[i, -len(item) :, :] = item.clone()
+                else:
+                    tensor[i, : len(item), :] = item.clone()
+            padding_length.append(tensor.shape[-1] - len(item))
+        return tensor, padding_length

special_tokens_map.json ADDED Viewed

	@@ -0,0 +1,112 @@

+{
+  "additional_special_tokens": [
+    "<unk>",
+    "<image>",
+    "</image>",
+    "<ref>",
+    "</ref>",
+    "<box>",
+    "</box>",
+    "<quad>",
+    "</quad>",
+    "<point>",
+    "</point>",
+    "<slice>",
+    "</slice>",
+    "<image_id>",
+    "</image_id>",
+    "<unit>",
+    "</unit>",
+    "<|reserved_0|>",
+    "<|reserved_1|>",
+    "<|reserved_2|>",
+    "<|reserved_3|>",
+    "<|reserved_4|>",
+    "<|reserved_5|>",
+    "<|reserved_6|>",
+    "<|reserved_7|>",
+    "<|reserved_8|>",
+    "<|reserved_9|>",
+    "<|reserved_10|>",
+    "<|reserved_11|>",
+    "<|reserved_12|>",
+    "<|reserved_13|>",
+    "<|reserved_14|>",
+    "<|reserved_15|>",
+    "<|reserved_16|>",
+    "<|reserved_17|>",
+    "<|reserved_18|>",
+    "<|reserved_19|>",
+    "<|reserved_20|>",
+    "<|reserved_21|>",
+    "<|reserved_22|>",
+    "<|reserved_23|>",
+    "<|reserved_24|>",
+    "<|reserved_25|>",
+    "<|reserved_26|>",
+    "<|reserved_27|>",
+    "<|reserved_28|>",
+    "<|reserved_29|>",
+    "<|reserved_30|>",
+    "<|reserved_31|>",
+    "<|reserved_32|>",
+    "<|reserved_33|>",
+    "<|reserved_34|>",
+    "<|reserved_35|>",
+    "<|reserved_36|>",
+    "<|reserved_37|>",
+    "<|reserved_38|>",
+    "<|reserved_39|>",
+    "<|reserved_40|>",
+    "<|reserved_41|>",
+    "<|reserved_42|>",
+    "<|reserved_43|>",
+    "<|reserved_44|>",
+    "<|reserved_45|>",
+    "<|reserved_46|>",
+    "<|reserved_47|>",
+    "<|reserved_48|>",
+    "<|reserved_49|>",
+    "<|reserved_50|>",
+    "<|reserved_51|>",
+    "<|reserved_52|>",
+    "<|reserved_53|>",
+    "<|reserved_54|>",
+    "<|reserved_55|>",
+    "<|reserved_56|>",
+    "<|reserved_57|>",
+    "<|reserved_58|>",
+    "<|reserved_59|>",
+    "<|reserved_60|>",
+    "<|reserved_61|>",
+    "<|reserved_62|>"
+  ],
+  "bos_token": {
+    "content": "<|im_start|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenization_minicpmv_fast.py ADDED Viewed

	@@ -0,0 +1,66 @@

+from transformers import Qwen2TokenizerFast
+class MiniCPMVTokenizerFast(Qwen2TokenizerFast):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.im_start = "<image>"
+        self.im_end = "</image>"
+        self.ref_start = "<ref>"
+        self.ref_end = "</ref>"
+        self.box_start = "<box>"
+        self.box_end = "</box>"
+        self.quad_start = "<quad>"
+        self.quad_end = "</quad>"
+        self.slice_start = "<slice>"
+        self.slice_end = "</slice>"
+        self.im_id_start = "<image_id>"
+        self.im_id_end = "</image_id>"
+    @property
+    def eos_id(self):
+        return self.eos_token_id
+    @property
+    def bos_id(self):
+        return self.bos_token_id
+    @property
+    def unk_id(self):
+        return self.unk_token_id
+    @property
+    def im_start_id(self):
+        return self.convert_tokens_to_ids(self.im_start)
+    @property
+    def im_end_id(self):
+        return self.convert_tokens_to_ids(self.im_end)
+    @property
+    def slice_start_id(self):
+        return self.convert_tokens_to_ids(self.slice_start)
+    @property
+    def slice_end_id(self):
+        return self.convert_tokens_to_ids(self.slice_end)
+    @property
+    def im_id_start_id(self):
+        return self.convert_tokens_to_ids(self.im_id_start)
+    @property
+    def im_id_end_id(self):
+        return self.convert_tokens_to_ids(self.im_id_end)
+    @property
+    def newline_id(self):
+        return self.convert_tokens_to_ids('\n')
+    @staticmethod
+    def escape(text: str) -> str:
+        return text
+    @staticmethod
+    def unescape(text: str) -> str:
+        return text

tokenizer.json ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:0ea5706e1afcf5774ae15138f8418dfd46b30558d6a2c9782f4eae9ff25341e0
+size 11825878

tokenizer_config.json ADDED Viewed

The diff for this file is too large to render. See raw diff

vocab.json ADDED Viewed

The diff for this file is too large to render. See raw diff