pytorch/hub

What it solves

PyTorch Hub is a repository of pre-trained models that allows users to easily discover and load models from various sources into PyTorch. It simplifies the process of making pre-trained models available to the community and sharing them in a standardized way.

How it works

It functions as a central registry. Model authors can submit their models to the Hub by adding a hubconf.py file to their own repository and creating a pull request to the pytorch/hub repository with a descriptive markdown file. Once merged, the model becomes discoverable on the PyTorch website.

Who it’s for

Researchers and developers who want to share their PyTorch models with others or users who want to load pre-trained models for use in their project without having to manually download and download weights manually.

Highlights

• own repository hosting: Model authors host their own weights and code; the Hub serves as a directory.
• standardized loading: Uses torch.hub.load(...) for a consistent interface for loading models.
• community-driven: Submission process via PRs to a central repository.
• CI verification: Includes sanity checks and automated tests to run python code blocks from the model's markdown files to ensure they work with the latest PyTorch release.