2371e46c89 | ||
---|---|---|
.gitattributes | ||
README.md | ||
config.json | ||
configuration.json | ||
configuration_llama.py | ||
generation_config.json | ||
model-00001-of-00004.safetensors | ||
model-00002-of-00004.safetensors | ||
model-00003-of-00004.safetensors | ||
model-00004-of-00004.safetensors | ||
model.safetensors.index.json | ||
modeling_llama.py | ||
special_tokens_map.json | ||
tokenizer.json | ||
tokenizer_config.json |
README.md
license |
---|
Apache License 2.0 |
Clone with HTTP
git clone https://www.modelscope.cn/FlagAlpha/Llama3-Chinese-8B-Instruct.git
Llama3-Chinese-8B
Llama3-Chinese-8B基于Llama3-8B的中文对话模型,由Llama中文社区和AtomEcho(原子回声)联合研发,我们会持续提供更新的模型参数,模型训练过程见(https://llama.family)。
模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库:https://github.com/LlamaFamily/Llama-Chinese
在线体验
如何使用
下载模型
git clone https://www.modelscope.cn/FlagAlpha/Llama3-Chinese-8B-Instruct.git
使用
import transformers
import torch
model_id = "./Llama3-Chinese-8B-Instruct"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.float16},
device="cuda",
)
messages = [{"role": "system", "content": ""}]
messages.append(
{"role": "user", "content": "介绍一下机器学习"}
)
prompt = pipeline.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
prompt,
max_new_tokens=512,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9
)
content = outputs[0]["generated_text"][len(prompt):]
print(content)