Model upload and sharing

Starting with v2.2.2, you can now upload and share your fine-tuned models with the community, using the CLI that’s built-in to the library.

First, create an account on Optionally, join an existing organization or create a new one. Then:

transformers-cli login
# log in using the same credentials as on

Upload your model:

transformers-cli upload ./path/to/pretrained_model/

# ^^ Upload folder containing weights/tokenizer/config
# saved via `.save_pretrained()`

transformers-cli upload ./config.json [--filename folder/foobar.json]

# ^^ Upload a single file
# (you can optionally override its filename, which can be nested inside a folder)

If you want your model to be namespaced by your organization name rather than your username, add the following flag to any command:

--organization organization_name

Your model will then be accessible through its identifier, a concatenation of your username (or organization name) and the folder name above:

# or if an org:

Please add a model card to the repo under model_cards/ with: model description, training params (dataset, preprocessing, hardware used, hyperparameters), evaluation results, intended uses & limitations, etc.

Your model now has a page on 🔥

Anyone can load it from code:

tokenizer = AutoTokenizer.from_pretrained("namespace/pretrained_model")
model = AutoModel.from_pretrained("namespace/pretrained_model")

List all your files on S3:

transformers-cli s3 ls

You can also delete unneeded files:

transformers-cli s3 rm …