Fastai
The fastai deep learning library includes documentation and setup guidance, including instructions for use with Google Colab.
About Fastai
Fastai is an open source deep learning library built on Python and PyTorch. It provides high-level components for tasks such as image classification, image segmentation, text sentiment analysis, recommendation, and tabular modeling, along with lower-level composable building blocks for building new approaches.
It can be used without local installation through Google Colab, including interactive notebook versions of documentation pages, or installed locally with pip after installing PyTorch. An editable install is documented for library development, and migration guides describe use with plain PyTorch, Ignite, Lightning, and Catalyst.
Key features
- Build image, text, tabular, and recommendation models with short code patterns
- Run documentation pages as interactive notebooks in Google Colab
- GPU-optimized computer vision library extendable in pure Python
- Two-way callback system to adjust data, model, or optimizer during training
- Type dispatch system with semantic type hierarchy for tensors
- Migration guides for plain PyTorch, Ignite, Lightning, and Catalyst
Best for: Practitioners and researchers building deep learning models with Python and PyTorch.
Good for
- Usable without local installation through Google Colab
- Documentation covers every class, function, and method
- Can be used alongside existing PyTorch data processing code
Fastai at a glance
- Website
- github.com/fastai/fastai
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for Developer Tools
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Fastai FAQ
How can I use fastai without installing it?
Use Google Colab and click "Open in colab" at the top of a documentation page, with the Colab runtime set to GPU.
How do I install fastai locally?
Install PyTorch first, then run pip install fastai.
Can I use fastai with existing PyTorch code?
Yes, you can keep existing data processing code and use fastai for training, with migration guides for plain PyTorch, Ignite, Lightning, and Catalyst.
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