Model upload and sharing¶
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 https://huggingface.co/join. Optionally, join an existing organization or create a new one. Then:
transformers-cli login # log in using the same credentials as on huggingface.co
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:
Your model will then be accessible through its identifier, a concatenation of your username (or organization name) and the folder name above:
"username/pretrained_model" # or if an org: "organization_name/pretrained_model"
Please add a README.md 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 huggingface.co/models 🔥
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 …