We accept submission to PyTorch hub through PR in hub repo. Once the PR is merged into master here, it will show up on the PyTorch website in 24 hrs.
- Add a hubconf.pyin your repo, following the instruction in torch.hub doc. Verify it's working correctly by runningtorch.hub.load(...)locally.
- Create a PR in pytorch/hubrepo. For each new model you have, create a<repo_owner>_<repo_name>_<title>.mdfile using this template.
- Currently we don't support hosting pretrained weights, users with pretrained weights need to host them properly themselves.
- In general we recommend one model per markdown file, models with similar structures like resnet18, resnet50should be placed in the same file.
- If you have images, place them in images/folder and link them correctly in the[images/featured_image_1/featured_image_2]fields above.
- We only support a pre-defined set of tags, currently they are listed in scripts/tags.py. We accept PRs to expand this set as needed.
- To test your PR locally, run the tests below.
python scripts/sanity_check.py
./scripts/run_pytorch.sh
- Our CI concatenates all python code blocks in one markdown file and runs it against the latest PyTorch release.
- Remember to mark your python code using ```pythonin your model's markdown file.
- If your dependenciesare not installed on our CI machine, add them in install.sh.
- If it fails, you can find a new temp.pyfile left in the repo to reproduce the failure.
 
- Remember to mark your python code using 
- We also provide a way to preview your model webpage through netlify bot. This bot builds your PR with the latestpytorch.github.iorepo and comments on your PR with a preview link. The preview will be updated as you push more commits to the PR.