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ModelZoo
Baichuan-13B_fastllm
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f62ba3ba
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f62ba3ba
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Jul 11, 2024
by
chenzk
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# Baichuan-13B
_fastllm
# Baichuan-13B
## 论文
...
...
@@ -33,7 +33,7 @@ Baichuan整体模型基于标准的Transformer结构,采用了和LLaMA一样
在光源可拉取推理的docker镜像,拉取方式如下:
```
docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:
1
.1
3.1
-centos7.6-dtk
-
23.
04
-py38
-latest
docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:
2
.1
.0
-centos7.6-dtk23.
10.1
-py38
```
### 容器启动
...
...
@@ -43,7 +43,7 @@ docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:1.13.1-centos7.6-dtk
```
# <container_name> 自定义容器名
# <project_path> 当前工程所在路径
docker run -it --name=<container_name> -v <project_path>:/work -w /work --device=/dev/kfd --device=/dev/dri --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --shm-size=16G --group-add
39
image.sourcefind.cn:5000/dcu/admin/base/pytorch:
1
.1
3.1
-centos7.6-dtk
-
23.
04
-py38
-latest
/bin/bash
docker run -it --name=<container_name> -v <project_path>:/work -w /work
--privileged -v /opt/hyhal:/opt/hyhal
--device=/dev/kfd --device=/dev/dri --security-opt seccomp=unconfined --cap-add=SYS_PTRACE
--ipc=host --network host
--shm-size=16G --group-add
video
image.sourcefind.cn:5000/dcu/admin/base/pytorch:
2
.1
.0
-centos7.6-dtk23.
10.1
-py38 /bin/bash
```
### 加载环境
...
...
@@ -51,7 +51,7 @@ docker run -it --name=<container_name> -v <project_path>:/work -w /work --device
进入容器后执行如下命令,加载运行环境变量
```
source /opt/dtk
-23.04
/cuda/env.sh
source /opt/dtk/cuda/env.sh
```
### 安装方法
...
...
@@ -74,6 +74,8 @@ python setup.py install
[
baichuan-inc/Baichuan2-13B-Chat · Hugging Face
](
https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat
)
### 模型转换
```
...
...
@@ -97,6 +99,15 @@ python cli_demo.py -p baichuan-13b-fp16.bin
# 简易webui,需要先安装streamlit-chat,并且需要在容器启动时映射streamlit的端口到外部网络
streamlit run web_demo.py baichuan-13b-fp16.bin
# 按照openai接口实现的api_server的实例:
# 需要先进入api_server_demo,安装所需依赖:
cd api_server_demo
pip install -r requirements.txt
# 运行api_server服务,使用-p指定转换后的模型文件,客户端代码可以参考openai-client.py实现:
python fastllm-openai.py -p ../baichuan-13b-fp16.bin
# 如果需要测试服务的并发性能,可以使用openai-client.py,修改其中的prompt和concurrencys变量值后执行:
python openai-client.py
```
### 推理性能测试
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@@ -133,6 +144,10 @@ chmod +x benchmark
`医疗,科研,金融,教育`
## 预训练权重
预训练权重快速下载中心:
[
SCNet AIModels
](
http://113.200.138.88:18080/aimodels
)
,项目中的预训练权重可从快速下载通道下载:
[
Baichuan-13B-Chat
](
http://113.200.138.88:18080/aimodels/Baichuan-13B-Chat
)
、
[
Baichuan2-13B-Chat
](
http://113.200.138.88:18080/aimodels/Baichuan2-13B-Chat
)
。
## 源码仓库及问题反馈
-
https://developer.hpccube.com/codes/modelzoo/baichuan-13b_fastllm
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