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Decision brief
A PyTorch-native post-training library focused on finetuning multimodal LLMs using state-of-the-art quantization techniques.
Good fit when
- - When you are working with the latest stable or preview nightly versions of PyTorch and need advanced finetuning for multimodal large language models (LLMs).
- - When leveraging torchao for cutting-edge quantization is essential to your model's performance post-training.
Avoid when
- - If you rely on a fixed, older version of PyTorch as Torchtune only supports the latest stable and preview nightly versions.
- - For scenarios where custom or non-PyTorch-native optimization methods are preferred over torchao’s quantization techniques.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
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Install
pip install torchtuneSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Torchtune is a post-training optimization and tuning library for PyTorch. It provides tools for finetuning multimodal large language models (LLMs) and uses the latest quantization techniques through torchao.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Aug 7, 2026
- Languages
- python
Source: github.language+pyproject.toml · Aug 7, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 7, 2026)
pip install torch torchvision torchaoSource link
Tags
README
Installation 🛠️
torchtune is only tested with the latest stable PyTorch release (currently 2.6.0) as well as the preview nightly version, and leverages torchvision for finetuning multimodal LLMs and torchao for the latest in quantization techniques; you should install these as well.
Install stable PyTorch, torchvision, torchao stable releases
pip install torch torchvision torchao pip install torchtune
---
# Install PyTorch, torchvision, torchao nightlies.
pip install --pre --upgrade torch torchvision torchao --index-url https://download.pytorch.org/whl/nightly/cu126 # full options are cpu/cu118/cu124/cu126/xpu/rocm6.2/rocm6.3/rocm6.4
pip install --pre --upgrade torchtune --extra-index-url https://download.pytorch.org/whl/nightly/cpu
You can also check out our install documentation for more information, including installing torchtune from source.
To confirm that the package is installed correctly, you can run the following command:
tune --help
And should see the following output:
usage: tune [-h] {ls,cp,download,run,validate} ...
Welcome to the torchtune CLI!
options:
-h, --help show this help message and exit
...
License
torchtune is released under the BSD 3 license. However you may have other legal obligations that govern your use of other content, such as the terms of service for third-party models.
For agents
This page has a .md twin and JSON over the API.