Preparation for installation
首先需要配置Python 3.9环境，建议使用conda管理虚拟环境。
Installation steps
- clone warehouse: Run it in the terminal
git clone https://github.com/OpenGVLab/InternVL.gitand enter the catalog - Creating a Virtual Environment: Use
conda create -n internvl python=3.9 -yCreating the Environment - Installation of basic dependencies: Run
pip install -r requirements.txtInstallation of core libraries
Optional Mounting
- mountingFlash-Attention以加速推理：
pip install flash-attn==2.3.6 - 安装MMDeploy用于生产部署：
mim install mmdeploy
多模态对话使用
下载模型（如InternVL2_5-8B）后，可以使用以下代码进行多模态对话：
from lmdeploy import pipeline
from lmdeploy.vl import load_image
model = 'OpenGVLab/InternVL2_5-8B'
image = load_image('tiger.jpeg')
pipe = pipeline(model)
response = pipe(('描述这张图片', image))
print(response.text)caveat
8B模型约需16GB GPU内存，处理高分辨率图像时可能需要更多资源。
This answer comes from the articleInternVL: Open Source Multimodal Large Model with Image, Video and Text Processing SupportThe
May not be reproduced without permission:AI productivity tools " 如何在本地安装和配置InternVL以进行多模态对话？
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