初始化项目，由ModelHub XC社区提供模型

Model: shanchen/llama3-8B-slerp-biomed-chat-chinese
Source: Original Platform

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- shanchen/llama3-8B-slerp-med-chinese
+- shenzhi-wang/Llama3-8B-Chinese-Chat
+base_model:
+- shanchen/llama3-8B-slerp-med-chinese
+- shenzhi-wang/Llama3-8B-Chinese-Chat
+license: llama3
+language:
+- zh
+- en
+---
+
+# llama3-8B-slerp-biomed-chat-chinese
+
+llama3-8B-slerp-biomed-chat-chinese is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [shanchen/llama3-8B-slerp-med-chinese](https://huggingface.co/shanchen/llama3-8B-slerp-med-chinese)
+* [shenzhi-wang/Llama3-8B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3-8B-Chinese-Chat)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: shanchen/llama3-8B-slerp-med-chinese
+        layer_range: [0,32]
+      - model: shenzhi-wang/Llama3-8B-Chinese-Chat
+        layer_range: [0,32]
+merge_method: slerp
+base_model: shenzhi-wang/Llama3-8B-Chinese-Chat
+parameters:
+  t:
+    - filter: self_attn
+      value: [0.3, 0.5, 0.5, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.7, 0.5, 0.5, 0.3]
+    - value: 0.5
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "shanchen/llama3-8B-slerp-biomed-chat-chinese"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, torch_dtype="auto", device_map="auto"
+)
+
+messages = [
+    {"role": "user", "content": "Can you speak Japanese?"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages, add_generation_prompt=True, return_tensors="pt"
+).to(model.device)
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=192 max#8192,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+response = outputs[0][input_ids.shape[-1]:]
+print(tokenizer.decode(response, skip_special_tokens=True))
+
+```