- adding support for Windows encoding by defaulting file load to UTF-8
- updated sentence-transformers version to 0.3.6
- beta support for model saving and loading
- new evaluation metrics based on coherence
- Introduced a method to predict the topics for a set of documents (supports multiple sampling to reduce variation)
- Adding some features to bert embeddings creation like increased batch size and progress bar
- Supporting training directly from lists without the need to deal with files
- Adding a simple quick preprocessing pipeline
- Updating sentence-transformers package to avoid errors
- Changed the encoding on file load for the SBERT embedding function
- Fixed bug over sparse matrices
- New feature handling sparse bow for optimized processing
- New method to return topic distributions for words
- Released models with the main features implemented
- First release on PyPI.