本節課可以讓同學們實踐 4 個主要內容，分別是：

1、部署?InternLM2-Chat-1.8B?模型進行智能對話

1.1安裝依賴庫：

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

?1.2下載?InternLM2-Chat-1.8B?模型

import os
from modelscope.hub.snapshot_download import snapshot_download# 創建保存模型目錄
os.system("mkdir /root/models")# save_dir是模型保存到本地的目錄
save_dir="/root/models"snapshot_download("Shanghai_AI_Laboratory/internlm2-chat-1_8b", cache_dir=save_dir, revision='v1.1.0')

?

1.3運行 cli_demo?

import torch
from transformers import AutoTokenizer, AutoModelForCausalLMmodel_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 (書生·浦語).
- InternLM (書生·浦語) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能實驗室). It is designed to be helpful, honest, and harmless.
- InternLM (書生·浦語) 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":breaklength = 0for response, _ in model.stream_chat(tokenizer, input_text, messages):if response is not None:print(response[length:], flush=True, end="")length = len(response)

2、部署實戰營優秀作品?八戒-Chat-1.8B?模型

• 八戒-Chat-1.8B：魔搭社區
• 聊天-嬛嬛-1.8B：OpenXLab浦源 - 模型中心
• Mini-Horo-巧耳：OpenXLab浦源 - 模型中心

git clone https://gitee.com/InternLM/Tutorial -b camp2

?執行下載模型：

python /root/Tutorial/helloworld/bajie_download.py

?待程序下載完成后，輸入運行命令：

?

streamlit run /root/Tutorial/helloworld/bajie_chat.py --server.address 127.0.0.1 --server.port 6006

?

?

3、通過?InternLM2-Chat-7B?運行?Lagent?智能體?Demo

?

Lagent 的特性總結如下：

• 流式輸出：提供 stream_chat 接口作流式輸出，本地就能演示酷炫的流式 Demo。
• 接口統一，設計全面升級，提升拓展性，包括：
  • 型號 ： 不論是 OpenAI API， Transformers 還是推理加速框架 LMDeploy 一網打盡，模型切換可以游刃有余;
  • Action： 簡單的繼承和裝飾，即可打造自己個人的工具集，不論 InternLM 還是 GPT 均可適配;
  • Agent：與 Model 的輸入接口保持一致，模型到智能體的蛻變只需一步，便捷各種 agent 的探索實現;
• 文檔全面升級，API 文檔全覆蓋。

下載模型:

git clone https://gitee.com/internlm/lagent.git
# git clone https://github.com/internlm/lagent.git
cd /root/demo/lagent
git checkout 581d9fb8987a5d9b72bb9ebd37a95efd47d479ac
pip install -e . # 源碼安裝

在 terminal 中輸入指令，構造軟鏈接快捷訪問方式：

ln -s /root/share/new_models/Shanghai_AI_Laboratory/internlm2-chat-7b /root/models/internlm2-chat-7b

打開?路徑下?文件，并修改對應位置 (71行左右) 代碼?:internlm2_agent_web_demo_hf.py

?

?修改模型地址：

運行前端代碼：

streamlit run /root/demo/lagent/examples/internlm2_agent_web_demo_hf.py --server.address 127.0.0.1 --server.port 6006

?

4、實踐部署?浦語·靈筆2?模型

補充環境包，選用?進行開發：50% A100

pip install timm==0.4.12 sentencepiece==0.1.99 markdown2==2.4.10 xlsxwriter==3.1.2 gradio==4.13.0 modelscope==1.9.5

下載?InternLM-XComposer 倉庫?相關的代碼資源：

cd /root/demo
git clone https://gitee.com/internlm/InternLM-XComposer.git
# git clone https://github.com/internlm/InternLM-XComposer.git
cd /root/demo/InternLM-XComposer
git checkout f31220eddca2cf6246ee2ddf8e375a40457ff626

?

?在?中輸入指令，構造軟鏈接快捷訪問方式：terminal

ln -s /root/share/new_models/Shanghai_AI_Laboratory/internlm-xcomposer2-7b /group_share/01/models/internlm-xcomposer2-7b
ln -s /root/share/new_models/Shanghai_AI_Laboratory/internlm-xcomposer2-vl-7b /group_share/01/models/internlm-xcomposer2-vl-7b

??圖文寫作實戰（開啟 50% A100 權限后才可開啟此章節）

cd /root/demo/InternLM-XComposer
python /root/demo/InternLM-XComposer/examples/gradio_demo_composition.py  \
--code_path /root/models/internlm-xcomposer2-7b \
--private \
--num_gpus 1 \
--port 6006

?

?

?

?

根據附錄 6.4 的方法，關閉并重新啟動一個新的?，繼續輸入指令，啟動?：terminalInternLM-XComposer2-vl

conda activate democd /root/demo/InternLM-XComposer
python gradio_demo_chat.py  \
--code_path /group_share/01/models/internlm-xcomposer2-vl-7b \
--private \
--num_gpus 1 \
--port 6006