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transformer/modeling_minimax_h3_pruned.py

@@ -112,6 +112,11 @@ class MiniMaxH3PrunedTransformer3DModel(MiniMaxH3Transformer3DModel):
         final_norm_eps: float = 1e-5,
         adaln_curve_grid: int = 1025,
         adaln_basis_dim: int = 2688,
+        # `config.json` carries `auto_map` so `AutoModel` can resolve this class through
+        # `trust_remote_code`. `ConfigMixin.extract_init_dict` drops `_`-prefixed keys and
+        # `quantization_config` before matching the config against `__init__`, but not
+        # `auto_map`, so it has to be accepted here or every load warns that it is unexpected.
+        auto_map: dict[str, str] | None = None,
     ) -> None:
         super().__init__(
             hidden_size=hidden_size,

transformer_ref/modeling_minimax_h3_pruned.py

@@ -112,6 +112,11 @@ class MiniMaxH3PrunedTransformer3DModel(MiniMaxH3Transformer3DModel):
         final_norm_eps: float = 1e-5,
         adaln_curve_grid: int = 1025,
         adaln_basis_dim: int = 2688,
+        # `config.json` carries `auto_map` so `AutoModel` can resolve this class through
+        # `trust_remote_code`. `ConfigMixin.extract_init_dict` drops `_`-prefixed keys and
+        # `quantization_config` before matching the config against `__init__`, but not
+        # `auto_map`, so it has to be accepted here or every load warns that it is unexpected.
+        auto_map: dict[str, str] | None = None,
     ) -> None:
         super().__init__(
             hidden_size=hidden_size,