Adapters 0.1.0

Blog post: https://adapterhub.ml/blog/2023/11/introducing-adapters/

With the new Adapters library, we fundamentally refactored the adapter-transformers library and added support for new models and adapter methods.

This version is compatible with Hugging Face Transformers version 4.35.2.

For a guide on how to migrate from adapter-transformers to Adapters have a look at https://docs.adapterhub.ml/transitioning.md.
Changes are given compared to the latest adapters-transformers v3.2.1.

New Models & Adapter Methods

• Add LLaMA model integration (@hSterz)
• Add X-MOD model integration (@calpt via #581)
• Add Electra model integration (@hSterz via #583, based on work of @amitkumarj441 and @pauli31 in #400)
• Add adapter output & parameter averaging (@calpt)
• Add Prompt Tuning (@lenglaender and @calpt via #595)
• Add Composition Support to LoRA and (IA)³ (@calpt via #598)

Breaking Changes

• Renamed bottleneck adapter configs and config strings. The new names can be found here: https://docs.adapterhub.ml/overview.html (@calpt)
• Removed the XModelWithHeads classes (@lenglaender) (XModelWithHeads have been deprecated since adapter-transformers version 3.0.0)

Changes Due to the Refactoring

• Refactored the implementation of all already supported models (@calpt, @lenglaender, @hSterz, @TimoImhof)
• Separate the model config (PretrainedConfig) from the adapters config (ModelAdaptersConfig) (@calpt)
• Updated the whole documentation, Jupyter Notebooks and example scripts (@hSterz, @lenglaender, @TimoImhof, @calpt)
• Introduced the load_model function to load models containing adapters. This replaces the Hugging Face from_pretrained function used in the adapter-transformers library (@lenglaender)
• Sharing more logic for adapter composition between different composition blocks (@calpt via #591)
• Added Backwards Compatibility Tests which allow for testing if adaptations of the codebase, such as Refactoring, impair the functionality of the library (@TimoImhof via #596)
• Refactored the EncoderDecoderModel by introducing a new mixin (ModelUsingSubmodelsAdaptersMixin) for models that contain other models (@lenglaender)
• Rename the class AdapterConfigBase into AdapterConfig (@hSterz via #603)

Fixes and Minor Improvements

• Fixed EncoderDecoderModel generate function (@lenglaender)
• Fixed deletion of invertible adapters (@TimoImhof)
• Automatically convert heads when loading with XAdapterModel (@calpt via #594)
• Fix training T5 adapter models with Trainer (@calpt via #599)
• Ensure output embeddings are frozen during adapter training (@calpt #537)