Update README.md

README.md

@@ -1,15 +1,18 @@
 ---
 base_model:
-- Sao10K/L3-8B-Stheno-v3.1
-- NousResearch/Meta-Llama-3-8B-Instruct
-- openchat/openchat-3.6-8b-20240522
-- hfl/llama-3-chinese-8b-instruct-v2-lora
+- wwe180/Llama3-10B-lingyang-v1
 library_name: transformers
 tags:
 - mergekit
 - merge
-
+license:
+- other
 ---
+
+#The model is experimental, so the results cannot be guaranteed.
+
+After simple testing, the effect is good, stronger than llama-3-8b!
+
 # merge
 
 This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
@@ -25,19 +28,24 @@ The following models were included in the merge:
 * [Sao10K/L3-8B-Stheno-v3.1](https://huggingface.co/Sao10K/L3-8B-Stheno-v3.1)
 * [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522) + [hfl/llama-3-chinese-8b-instruct-v2-lora](https://huggingface.co/hfl/llama-3-chinese-8b-instruct-v2-lora)
 
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-slices:
-  - sources:
-      - model: "Sao10K/L3-8B-Stheno-v3.1"
-        layer_range: [0, 22]
-  - sources:
-      - model: "openchat/openchat-3.6-8b-20240522+hfl/llama-3-chinese-8b-instruct-v2-lora"
-        layer_range: [10,32]
-merge_method: passthrough
-base_model: "NousResearch/Meta-Llama-3-8B-Instruct"
-dtype: bfloat16
-```
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Llama3-10B-lingyang-v1"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+