llama3-8B-slerp-biomed-chat-chinese
llama3-8B-slerp-biomed-chat-chinese is a merge of the following models using LazyMergekit:
🧩 Configuration
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
!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))