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1、使用开源的大模型服务搭建属于自己的模型服务;
2、调优自己的大模型;
采用通义千问模型,https://github.com/QwenLM/Qwen
1、下载模型文件
- mkdir -p /data/qwen
- cd /data/qwen
- git clone --depth 1 https://www.modelscope.cn/qwen/Qwen-14B-Chat.git
- # 小内存机器下载1.8B参数的,14B需要几十内存
- # git clone --depth 1 https://www.modelscope.cn/qwen/Qwen-1_8B-Chat.git
2、下载使用docker 镜像
docker pull qwenllm/qwen
3、启动脚本
https://github.com/QwenLM/Qwen/blob/main/docker/docker_web_demo.sh
- # 修改如下内容
- IMAGE_NAME=qwenllm/qwen
- QWEN_CHECKPOINT_PATH=/data/qwen/Qwen-14B-Chat
- PORT=8000
- CONTAINER_NAME=qwen
4、运行
访问http://localhost:8080 即可
sh docker_web_demo.sh
输出如下,可以查看容器日志是否报错。
- Successfully started web demo. Open '...' to try!
- Run `docker logs ...` to check demo status.
- Run `docker rm -f ...` to stop and remove the demo.
效果
https://github.com/QwenLM/Qwen/blob/main/README_CN.md
1、运行报错
去掉docker_web_demo.sh中--gpus all
docker: Error response from daemon: could not select device driver "" with capabilities: [[gpu]].
2、Error while deserializing header: HeaderTooLarge
先安装yum install git-lfs 在下载模型文件,模型是git大文件管理,需要git-lfs的支持。
Traceback (most recent call last):
File "web_demo.py", line 209, in <module>
main()
File "web_demo.py", line 203, in main
model, tokenizer, config = _load_model_tokenizer(args)
File "web_demo.py", line 50, in _load_model_tokenizer
model = AutoModelForCausalLM.from_pretrained(
File "/usr/local/lib/python3.8/dist-packages/transformers/models/auto/auto_factory.py", line 511, in from_pretrained
return model_class.from_pretrained(
File "/usr/local/lib/python3.8/dist-packages/transformers/modeling_utils.py", line 3091, in from_pretrained
) = cls._load_pretrained_model(
File "/usr/local/lib/python3.8/dist-packages/transformers/modeling_utils.py", line 3456, in _load_pretrained_model
state_dict = load_state_dict(shard_file)
File "/usr/local/lib/python3.8/dist-packages/transformers/modeling_utils.py", line 458, in load_state_dict
with safe_open(checkpoint_file, framework="pt") as f:
safetensors_rust.SafetensorError: Error while deserializing header: HeaderTooLarge
3、Cannot allocate memory
内存不足,可以尝试选择1_8B小参数的模型。
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