部署 InternLM2-Chat-1.8B 模型进行智能对话
环境配置
进入开发机后,在 terminal 中输入环境配置命令
studio-conda -o internlm-base -t demo
上面命令执行完后,conda会多一个虚拟环境
使用conda activate demo切换环境后,继续后面操作
安装环境依赖包
执行下面命令安装环境依赖包
pip install huggingface-hub==0.17.3
pip install transformers==4.34
pip install psutil==5.9.8
pip install accelerate==0.24.1
pip install streamlit==1.32.2
pip install matplotlib==3.8.3
pip install modelscope==1.9.5
pip install sentencepiece==0.1.99
使用 pip list 查看是否安装好
下载 InternLM2-Chat-1.8B 模型
按路径创建文件夹,并进入到对应文件目录中:
mkdir -p /root/demo
touch /root/demo/cli_demo.py
touch /root/demo/download_mini.py
通过左侧文件夹栏目,双击进入 demo 文件夹。
import os
from modelscope.hub.snapshot_download import snapshot_download
# 创建保存模型目录
os.system("mkdir /root/models")
# save_dir是模型保存到本地的目录
save_dir="/root/models"
snapshot_download("Shanghai_AI_Laboratory/internlm2-chat-1_8b",
cache_dir=save_dir,
revision='v1.1.0')
执行命令,下载模型参数文件:
python /root/demo/download_mini.py
或者直接通过vscode执行,
- 点击左下角的select interpret
- 选择创建的demo虚拟环境
- 点击右上角的执行按钮
下载过程
运行 cli_demo
双击打开 /root/demo/cli_demo.py 文件,复制以下代码:
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name_or_path = "/root/models/Shanghai_AI_Laboratory/internlm2-chat-1_8b"
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True, device_map='cuda:0')
model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype=torch.bfloat16, device_map='cuda:0')
model = model.eval()
system_prompt = """You are an AI assistant whose name is InternLM (书生·浦语).
- InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.
- InternLM (书生·浦语) can understand and communicate fluently in the language chosen by the user such as English and 中文.
"""
messages = [(system_prompt, '')]
print("=============Welcome to InternLM chatbot, type 'exit' to exit.=============")
while True:
input_text = input("\nUser >>> ")
input_text = input_text.replace(' ', '')
if input_text == "exit":
break
length = 0
for response, _ in model.stream_chat(tokenizer, input_text, messages):
if response is not None:
print(response[length:], flush=True, end="")
length = len(response)
输入命令,执行 Demo 程序:
conda activate demo
python /root/demo/cli_demo.py
实战:部署实战营优秀作品 八戒-Chat-1.8B 模型
下载模型
使用 git 命令来获得仓库内的 Demo 文件:
cd /root/
git clone https://gitee.com/InternLM/Tutorial -b camp2
# git clone https://github.com/InternLM/Tutorial -b camp2
cd /root/Tutorial
下载运行 Chat-八戒 Demo
使用conda activate demo切换环境后,在 Web IDE 中执行 bajie_download.py:
python /root/Tutorial/helloworld/bajie_download.py
待程序下载完成后,输入运行命令:
streamlit run /root/Tutorial/helloworld/bajie_chat.py --server.address 127.0.0.1 --server.port 6006
待程序运行的同时,对端口环境配置本地 PowerShell 。使用快捷键组合 Windows + R(Windows 即开始菜单键)打开指令界面,并输入命令,按下回车键。
最好提前配置好ssh,可以免密码登录
ssh -CNg -L 6006:127.0.0.1:6006 root@ssh.intern-ai.org.cn -p 38455
打开 http://127.0.0.1:6006 后,等待加载完成即可进行对话,键入内容示例如下:
你好,请自我介绍