AI Skill Hub 强烈推荐:unsloth Agent工作流 是一款优质的Agent工作流。在 GitHub 上收获超过 64.1k 颗 Star,AI 综合评分 8.2 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。
Web UI工作流平台,支持Gemma、Qwen等开源大模型的训练和推理。提供可视化界面简化模型微调流程,适合机器学习工程师和研究人员快速部署和优化AI模型。
unsloth Agent工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
Web UI工作流平台,支持Gemma、Qwen等开源大模型的训练和推理。提供可视化界面简化模型微调流程,适合机器学习工程师和研究人员快速部署和优化AI模型。
unsloth Agent工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:pip 安装(推荐)
pip install unsloth
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install unsloth
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/unslothai/unsloth
cd unsloth
pip install -e .
# 验证安装
python -c "import unsloth; print('安装成功')"
# 命令行使用
unsloth --help
# 基本用法
unsloth input_file -o output_file
# Python 代码中调用
import unsloth
# 示例
result = unsloth.process("input")
print(result)
# unsloth 配置文件示例(config.yml) app: name: "unsloth" debug: false log_level: "INFO" # 运行时指定配置文件 unsloth --config config.yml # 或通过环境变量配置 export UNSLOTH_API_KEY="your-key" export UNSLOTH_OUTPUT_DIR="./output"
<p align="center"> <a href="#-features">Features</a> • <a href="#-install">Quickstart</a> • <a href="#-free-notebooks">Notebooks</a> • <a href="https://unsloth.ai/docs">Documentation</a> </p> <br> <a href="https://unsloth.ai/docs/new/studio"> <img alt="unsloth studio ui homepage" src="https://github.com/user-attachments/assets/53ae17a9-d975-44ef-9686-efb4ebd0454d" style="max-width: 100%; margin-bottom: 0;"></a>
Unsloth Studio (Beta) lets you run and train text, audio, embedding, vision models on Windows, Linux and macOS.
Unsloth can be used in two ways: through Unsloth Studio, the web UI, or through Unsloth Core, the code-based version. Each has different requirements.
The below advanced instructions are for Unsloth Studio. For Unsloth Core advanced installation, view our docs. #### Developer / Nightly / Experimental installs: macOS, Linux, WSL: The developer install builds from the main branch, which is the latest (nightly) source.
git clone https://github.com/unslothai/unsloth
cd unsloth
./install.sh --local
unsloth studio -p 8888 To install into an isolated location (its own virtual env, auth/, studio.db, cache and llama.cpp build), set UNSLOTH_STUDIO_HOME and pass it again at launch: UNSLOTH_STUDIO_HOME="$PWD/.studio" ./install.sh --local
UNSLOTH_STUDIO_HOME="$PWD/.studio" unsloth studio -p 8888 Then to update : cd unsloth && git pull
./install.sh --local
unsloth studio -p 8888
#### Developer / Nightly / Experimental installs: Windows PowerShell: The developer install builds from the main branch, which is the latest (nightly) source.
git clone https://github.com/unslothai/unsloth.git
cd unsloth
Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
.\install.ps1 --local
unsloth studio -p 8888 To install into an isolated location (its own virtual env, auth/, studio.db, cache and llama.cpp build), set UNSLOTH_STUDIO_HOME and pass it again at launch: $env:UNSLOTH_STUDIO_HOME="$PWD\.studio"; .\install.ps1 --local
$env:UNSLOTH_STUDIO_HOME="$PWD\.studio"; unsloth studio -p 8888 Then to update : cd unsloth; git pull
.\install.ps1 --local
unsloth studio -p 8888
#### Remote access: --secure (HTTPS tunnel) vs raw port By default unsloth studio binds to 127.0.0.1 (this machine only). To reach it from another device, pick one of:
- --secure (recommended): serve only through a free Cloudflare HTTPS link. Studio stays bound to localhost and the tunnel provides the public URL; it fails closed (does not start) if the tunnel can't come up, so the raw port is never exposed.
unsloth studio --secure -p 8888 - -H 0.0.0.0: bind the raw port on all network interfaces, reachable from anywhere on the network. Only use this on a trusted network. unsloth studio -H 0.0.0.0 -p 8888
Server-side tools (web search, Python and terminal code execution) run as your user and are on by default. Anyone who can reach the server with the API key can run code on this machine, so keep your API key private and pass --disable-tools when exposing Studio.
#### Advanced launch options Installer options can be passed as environment variables. On macOS, Linux and WSL place the variable after the pipe so the shell passes it to sh; on Windows set it with $env: before piping to iex.
Skip PyTorch (GGUF-only mode):
curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_NO_TORCH=1 sh $env:UNSLOTH_NO_TORCH=1; irm https://unsloth.ai/install.ps1 | iex
Pin the Python version:
curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_PYTHON=3.12 sh $env:UNSLOTH_PYTHON='3.12'; irm https://unsloth.ai/install.ps1 | iex
Install to a custom location with UNSLOTH_STUDIO_HOME:
curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_STUDIO_HOME=/abs/path sh $env:UNSLOTH_STUDIO_HOME='C:\path'; irm https://unsloth.ai/install.ps1 | iex
On macOS, the installer defaults to the system certificate store (UV_SYSTEM_CERTS=1) so uv trusts the CAs in your Keychain, needed behind TLS-inspecting proxies (Cisco Umbrella, Zscaler, etc.). Opt out with:
curl -fsSL https://unsloth.ai/install.sh | UV_SYSTEM_CERTS=0 sh
Point the frontend build at a corporate npm mirror/proxy with UNSLOTH_NPM_REGISTRY (for the developer install behind a firewall that blocks registry.npmjs.org):
UNSLOTH_NPM_REGISTRY=https://artifactory.example.com/api/npm/npm/ ./install.sh --local $env:UNSLOTH_NPM_REGISTRY='https://artifactory.example.com/api/npm/npm/'; .\install.ps1 --local It is threaded as --registry into the Studio frontend npm/bun installs; the supply-chain locks (7-day min-release-age, exact version pins) stay in force.
Cap Studio's native CPU thread pools on high-core hosts: UNSLOTH_CPU_THREADS=8 unsloth studio -p 8888.
#### Uninstall The recommended way to fully remove Unsloth Studio is the matching uninstall script for your OS. It stops any running servers, removes the install dir, the launcher data dir, the desktop shortcut, and any platform-specific entries (macOS .app bundle + Launch Services on Mac; Start Menu, HKCU\Software\Unsloth registry key and user PATH entries on Windows):
curl -fsSL https://raw.githubusercontent.com/unslothai/unsloth/main/scripts/uninstall.sh | shirm https://raw.githubusercontent.com/unslothai/unsloth/main/scripts/uninstall.ps1 | iexIf you only want to drop the install dir and keep the launcher/shortcut for a later reinstall, you can instead run rm -rf ~/.unsloth/studio (Mac/Linux/WSL) or Remove-Item -Recurse -Force "$HOME\.unsloth\studio" (Windows). The model cache at ~/.cache/huggingface is not touched by any of these.
For more info, see our docs.
You can delete old model files either from the bin icon in model search or by removing the relevant cached model folder from the default Hugging Face cache directory. By default, HF uses:
~/.cache/huggingface/hub/%USERPROFILE%\.cache\huggingface\hub\成熟的开源模型训练平台,集成度高、社区活跃。6万+stars证明其实用价值,适合专业用户和团队使用。
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建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
总体来看,unsloth Agent工作流 是一款质量优秀的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | unsloth |
| 原始描述 | 开源AI工作流:Unsloth Studio is a web UI for training and running open models like Gemma 4, Qw。⭐64.1k · Python |
| Topics | 模型训练微调开源模型Web工作流深度学习 |
| GitHub | https://github.com/unslothai/unsloth |
| License | Apache-2.0 |
| 语言 | Python |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
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