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SWIFT安装

Wheel包安装

可以使用pip进行安装：

# 推荐
pip install 'ms-swift'
# 使用评测
pip install 'ms-swift[eval]' -U
# 全能力
pip install 'ms-swift[all]' -U

源代码安装

# pip install git+https://github.com/modelscope/ms-swift.git

# 全能力
# pip install "git+https://github.com/modelscope/ms-swift.git#egg=ms-swift[all]"

git clone https://github.com/modelscope/ms-swift.git
cd ms-swift
pip install -e .

# 全能力
# pip install -e '.[all]'

旧版本

SWIFT在3.0版本开始进行了不兼容式重构，如果需要使用2.x旧版本，请执行如下命令进行安装：

pip install ms-swift==2.*

镜像

docker可以查看这里。

# swift3.9.1
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.8.1-py311-torch2.8.0-vllm0.11.0-modelscope1.31.0-swift3.9.1
modelscope-registry.cn-beijing.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.8.1-py311-torch2.8.0-vllm0.11.0-modelscope1.31.0-swift3.9.1
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.8.1-py311-torch2.8.0-vllm0.11.0-modelscope1.31.0-swift3.9.1

# swift3.8.3
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.6.3-py311-torch2.7.1-vllm0.10.1.1-modelscope1.29.2-swift3.8.3
modelscope-registry.cn-beijing.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.6.3-py311-torch2.7.1-vllm0.10.1.1-modelscope1.29.2-swift3.8.3
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.6.3-py311-torch2.7.1-vllm0.10.1.1-modelscope1.29.2-swift3.8.3

# swift3.7.2
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.6.3-py311-torch2.7.1-vllm0.10.0-modelscope1.28.2-swift3.7.2
modelscope-registry.cn-beijing.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.6.3-py311-torch2.7.1-vllm0.10.0-modelscope1.28.2-swift3.7.2
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.6.3-py311-torch2.7.1-vllm0.10.0-modelscope1.28.2-swift3.7.2

# swift3.6.4
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py310-torch2.6.0-vllm0.8.5.post1-modelscope1.28.1-swift3.6.4
modelscope-registry.cn-beijing.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py310-torch2.6.0-vllm0.8.5.post1-modelscope1.28.1-swift3.6.4
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py310-torch2.6.0-vllm0.8.5.post1-modelscope1.28.1-swift3.6.4
历史镜像 
# swift3.5.3
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py310-torch2.6.0-vllm0.8.5.post1-modelscope1.27.1-swift3.5.3
modelscope-registry.cn-beijing.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py310-torch2.6.0-vllm0.8.5.post1-modelscope1.27.1-swift3.5.3
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py310-torch2.6.0-vllm0.8.5.post1-modelscope1.27.1-swift3.5.3

# swift3.4.1.post1
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py311-torch2.6.0-vllm0.8.5.post1-modelscope1.26.0-swift3.4.1.post1
modelscope-registry.cn-beijing.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py311-torch2.6.0-vllm0.8.5.post1-modelscope1.26.0-swift3.4.1.post1
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py311-torch2.6.0-vllm0.8.5.post1-modelscope1.26.0-swift3.4.1.post1

# swift3.3.0.post1
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py311-torch2.6.0-vllm0.8.3-modelscope1.25.0-swift3.3.0.post1
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py311-torch2.6.0-vllm0.8.3-modelscope1.25.0-swift3.3.0.post1

# swift3.2.2
modelscope-registry.us-west-1.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.4.0-py311-torch2.5.1-modelscope1.25.0-swift3.2.2

更多镜像可以查看这里。

支持的硬件

硬件环境 备注
A10/A100/H100
RTX20/30/40系列
T4/V100 部分模型出现NAN
Ascend NPU 部分模型出现NAN或算子不支持
MPS 参考issue 4572
CPU

运行环境

范围 推荐 备注
python >=3.9 3.10/3.11
cuda cuda12 使用cpu、npu、mps则无需安装
torch >=2.0 2.7.1
transformers >=4.33 4.56.2
modelscope >=1.23
peft >=0.11,<0.18
flash_attn 2.8.1/3.0.0b1
trl >=0.15,<0.24 0.20.0 RLHF
deepspeed >=0.14 0.17.5 训练
vllm >=0.5.1 0.10.1.1 推理/部署
sglang >=0.4.6 0.4.10.post2 推理/部署
lmdeploy >=0.5 0.9.2.post1 推理/部署
evalscope >=1.0 评测
gradio 5.32.1 Web-UI/App

更多可选依赖可以参考这里。

Notebook环境

Swift支持训练的绝大多数模型都可以在A10显卡上使用，用户可以使用ModelScope官方提供的免费显卡资源：

  1. 进入ModelScope官方网站并登录。
  2. 点击左侧的我的Notebook并开启一个免费GPU实例。
  3. 愉快地薅A10显卡羊毛。