There are many ways in which you can contribute to AdapterHub and the adapter-transformers library.
This includes code contributions such as:
- implementing new adapter methods
- adding support for new Transformer
- fixing open issues
as well as non-code contributions such as:
- training and uploading adapters to the Hub
- writing documentation and blog posts
- helping others with their issues and questions
Whichever way you'd like to contribute, you're very welcome to do so!
To get started with writing code for adapter-transformers, you'd want to set up the project on a local/ development environment.
adapter-transformers closely follows the original HuggingFace Transformers repository in many aspects.
As they already provide a great guide on setting up the project and the general contribution process, we refer to their contributing guide here.
Some additional notes are given below.
adapter-transformers uses the same code quality checks as HuggingFace Transformers.
Therefore, make sure to pass all the tests run using
$ make qualityto pass our CI pipeline.
Besides the commands for formatting, style checking and testing mentioned in the HuggingFace contributing guide, you can run all tests specific to adapter-transformers as follows:
$ make test-adaptersThis corresponds to the tests run in our CI pipeline.
Below we refer to more detailed explanations of some typical contribution scenarios.
How to integrate new efficient fine-tuning/ adapter methods to adapter-transformers is described at https://docs.adapterhub.ml/contributing/adding_adapter_methods.html.
How to add adapter support to a model type already supported by HuggingFace Transformers is described at https://docs.adapterhub.ml/contributing/adding_adapters_to_a_model.html.
How to make your own trained adapters accessible via AdapterHub is described at https://docs.adapterhub.ml/hub_contributing.html.