adapter-transformers 3.2.1.post0

A friendly fork of HuggingFace's Transformers, adding Adapters to PyTorch language models

The adapter-hub/adapters repo was created 3 years ago and the last code push was 23 hours ago.
The project is very popular with an impressive 2369 github stars!

How to Install adapter-transformers

You can install adapter-transformers using pip

pip install adapter-transformers

or add it to a project with poetry

poetry add adapter-transformers

Package Details

Author

Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Hannah Sterz, Leon Engländer, based on work by the HuggingFace team and community

License

Apache

Homepage

https://github.com/adapter-hub/adapter-transformers

PyPi:

https://pypi.org/project/adapter-transformers/

GitHub Repo:

https://github.com/adapter-hub/adapter-transformers

Classifiers

• Scientific/Engineering/Artificial Intelligence

Related Packages

Errors

A list of common adapter-transformers errors.

Code Examples

Here are some adapter-transformers code examples and snippets.

GitHub Issues

The adapter-transformers package has 56 open issues on GitHub

• How to configure a new model to adapt adapter within?
• The wiki data that is used on MLM
• About using both Fusion and Stack
• Add support for DebertaV2/V3
• Adapter Fusion with parallel inference of the individual adapters
• Add ForwardContext to wrap model forward pass
• Unify & simplify model adapter integration
• For the task of translation, is it only applicable to model facebook/bart-base?
• Unify built-in & custom head implementation
• MAD-G
• Train adapters without Hugging Face Trainer scripts
• reduction_factor -> bottleneck_size

See more issues on GitHub