Unsloth: desktop app and library to run and train models, README overview
The README presents Unsloth as an app and library for running and fine-tuning models.
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- commit 8e8c91018dea82d2c90b58a4889d18d7dfe3b0a6 · source_revision · · availability: unknown
- Unsloth: desktop app and library to run and train models, README overview · repository · · availability: available (checked 2026-11-07)
Source: https://github.com/unslothai/unsloth
What it supplies: The README presents Unsloth as an app and library for running and fine-tuning models.
Useful for: - Run models in a desktop app.
- Train models from code with Unsloth Core.
First action: - Download the desktop app, or run the install script.
- For code, create a uv environment and run uv pip install unsloth.
Prerequisites and limits: The README example uses Python 3.13 in a uv environment and pins a Python version with an environment variable.
- Piping an install script to a shell runs remote code; inspect it or use the download.
- AGPL-3.0 components have network-use obligations.
Source-documented: core under Apache 2.0, some optional components such as the Studio UI under AGPL-3.0. Check which parts you use.
Written from the README text only. Statements are as the README gives them; nothing was installed or run.
Based on opening, get-started, Unsloth Core install and licensing README text only; other sections were not read. Nothing was installed or run.
Source inspected: https://raw.githubusercontent.com/unslothai/unsloth/8e8c91018dea82d2c90b58a4889d18d7dfe3b0a6/README.md ; 25010 bytes ; sha256 5c5f239e1c65716d58758fe3f8e611c49337fca3f54d5f2e71a517f72c76784b ; 5 exact pinned excerpts in the draft pin map
Structured fields
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"usefulness": "- Run models in a desktop app.\n- Train models from code with Unsloth Core.",
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}Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | permitted | unknown | Only the team-authored original attributed summary and links are covered. Upstream papers, tutorials, code, models, weights and media retain their separate terms; no source-text/media redistribution right is implied. |