- Added PyTorch as a backend
nlp_architectCLI for training/running/process models and scripts
nlp_architect.procedurespackage for creating procedures/scripts for doing scripted work with NLP architect.
- S3 URL caching of pre-trained models
- Many additions/refactors/base classes reflecting new API (WIP)
pytorch-transformerslibrary into NLP Architect's model package.
- Created a base transformer class for training transformer-based models
- Added sequence/token classification models
Optimization related models
- Added a base transformer model for training quantized (8bit) BERT models
- Added distillation process from Transformer models into CNN/LSTM based token classification models
NLP related additions
- Added GLUE benchmark tasks
- Added CNN-LSTM and ID-CNN token classification models (pytorch backend)
- Updated documentation website to reflect 0.5 release
- Updated website with logo and matching style