Release adapter-transformers v3.2.0 · adapter-hub/adapters

Based on transformers v4.26.1

New

Add support for adapter configuration strings (@calpt via #465, #486)
This enables you to easily configure adapter configs. To create a Pfeiffer adapter with reduction factor 16 you can know use pfeiffer[reduction_factor=16]. Especially for experiments using different hyperparameters or the example scripts, this can come in handy. Learn more
Add for Stack, Parallel & BatchSplit composition to prefix tuning (@calpt via #476)
In previous adapter-transformers versions, you could combine multiple bottleneck adapters. You could use them in parallel or stack them. Now, this is also possible for prefix-tuning adapters. Add multiple prefixes to the same model to combine the functionality of multiple adapters (Stack) or perform several tasks simultaneously (Parallel, BatchSplit) Learn more
Enable parallel sequence generation with adapters (@calpt via #436)

Removal of the MultiLingAdapterArguments class. Use the AdapterArguments class and setup_adapter_training method instead. Learn more.
Upgrade of underlying transformers version to 4.26.1 (@calpt via #455, @hSterz via #503)

Fixes for GLUE & dependency parsing example script (@calpt via #430, #454)
Fix access to shared parameters of compacter (e.g. during sequence generation) (@calpt via #440)
Fix reference to adapter configs in T5EncoderModel (@calpt via #437)
Fix DeBERTa prefix tuning with enabled relative attention (@calpt via #451)
Fix gating for prefix tuning layers (@calpt via #471)
Fix input to T5 adapter layers (@calpt via #479)
Fix AdapterTrainer hyperparameter tuning (@dtuit via #482)
Move loading best adapter to AdapterTrainer class (@MaBeHen via #487)
Make HuggingFace Hub Mixin work with newer utilities (@Helw150 via #473)
Only compute fusion reg loss if fusion layer is trained (@calpt via #505)