Inspired by transformers' adoption of the auto-models, we created an AutoEncoder class that allows you to easily get the relevant models. Not to be confused with the autoencoder architecture.
The relevant models can be found here:
from vectorhub import AutoEncoder
encoder = AutoEncoder('text/bert')
encoder.encode("Hi...")To view the list of available models, you can call:
import vectorhub as vh
vh.list_available_auto_models()When you instantiate the autoencoder, you will need to pip install the relevant module. The requirements here can be given here.
The list of supported models are:
['text/albert', 'text/bert', 'text/labse', 'text/use', 'text/use-multi', 'text/use-lite', 'text/legal-bert', 'audio/fairseq', 'audio/speech-embedding', 'audio/trill', 'audio/trill-distilled', 'audio/vggish', 'audio/yamnet', 'audio/wav2vec', 'image/bit', 'image/bit-medium', 'image/inception', 'image/inception-v2', 'image/inception-v3', 'image/inception-resnet', 'image/mobilenet', 'image/mobilenet-v2', 'image/resnet', 'image/resnet-v2', 'text_text/use-multi-qa', 'text_text/use-qa', 'text_text/dpr', 'text_text/lareqa-qa]