# Model Overview¶

This page gives an overview of the Transformer models currently supported by adapter-transformers. The table below further shows which model architectures support which adaptation methods and which features of adapter-transformers.

Note

Each supported model architecture X typically provides a class XAdapterModel for usage with AutoAdapterModel. Additionally, it is possible to use adapters with the model classes already shipped with HuggingFace Transformers. E.g., for BERT, this means adapter-transformers provides a BertAdapterModel class, but you can also use BertModel, BertForSequenceClassification etc. together with adapters.

Model (Bottleneck)
Prefix
Tuning
Fusion
Invertible
Parallel
block
ALBERT
BART
BEIT
BERT-Generation
BERT
CLIP
DeBERTa
DeBERTa-v2
DistilBERT
Encoder Decoder (*) (*) (*) (*) (*) (*)
GPT-2
GPT-J
MBart
RoBERTa
T5
ViT
XLM-RoBERTa

(*) If the used encoder and decoder model class are supported.

Missing a model architecture you’d like to use? adapter-transformers can be easily extended to new model architectures as described in Adding Adapters to a Model. Feel free to open an issue requesting support for a new architecture. We very much welcome pull requests adding new model implementations!