书生浦语--第二节作业笔记合集

Smiling & Weeping

　　　　　　　　　　　　　　　　　　---- 真想拥有一个稳定的情绪

笔记： 

部署兴趣Demo首先需要部署开发机环境

进入开发机后，在 terminal 中输入环境配置命令 (配置环境时间较长，需耐心等待)：

studio-conda -o internlm-base -t demo
# 与 studio-conda 等效的配置方案
# conda create -n demo python==3.10 -y
# conda activate demo
# conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.7 -c pytorch -c nvidia

配置完成后进入环境：

conda activate demo

输入以下命令，完成环境包的安装：

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

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
cd /root/demo

双击打开 /root/demo/download_mini.py 文件，复制以下代码：

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

 

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

作业：

基础作业：

InternLM2-1.8B生成300字小故事的效果图：

 优秀学员进阶作业部分：

• 熟悉 huggingface 下载功能，使用 huggingface_hub python 包，下载 InternLM2-Chat-7B 的 config.json 文件到本地（需截图下载过程）

 

• 完成 浦语·灵笔2 的 图文创作 及 视觉问答 部署（需截图）