

It is worth spending some time to create fitting model cards for each checkpoint. The model cards should highlight the
specific characteristics of this particular checkpoint, e.g. On which dataset was the checkpoint
pretrained/fine-tuned on? On what down-stream task should the model be used? And also include some code on how to
correctly use the model.
13. (Optional) Add notebook
It is very helpful to add a notebook that showcases in-detail how brand_new_bert can be used for inference and/or
fine-tuned on a downstream task. This is not mandatory to merge your PR, but very useful for the community.
14. Submit your finished PR
You're done programming now and can move to the last step, which is getting your PR merged into main. Usually, the
Hugging Face team should have helped you already at this point, but it is worth taking some time to give your finished
PR a nice description and eventually add comments to your code, if you want to point out certain design choices to your
reviewer.
Share your work!!
Now, it's time to get some credit from the community for your work! Having completed a model addition is a major
contribution to Transformers and the whole NLP community. Your code and the ported pre-trained models will certainly be
used by hundreds and possibly even thousands of developers and researchers. You should be proud of your work and share
your achievements with the community.
You have made another model that is super easy to access for everyone in the community! 🤯