Dependencies for universal sentence encoder and BERT sentence transformer options are now optional. With `pip install top2vec[sentence-encoders]` and `pip install top2vec[sentence_transformers]`
Faster cosine similarity.
1.0.15
The `verbose` parameter will be set to True by default.
Fixed a bug that stopped showing logging updates after downloading pre-trained models.
1.0.13
1.0.12
Top2Vec now has an option to choose the embedding model with `doc2vec`, `universal-sentence-encoder`, `universal-sentence-encoder-multilingual`, and `distiluse-base-multilingual-cased` as the options.
A `get_documents_topics` method was added.
1.0.11
Added a method for deleting documents from model.
Fixed bug when using `corpus_file` that resulted in documents getting dropped. Fixed bug when using `add_documents` and `delete_documents` which resulted in improper ordering of topic words.
1.0.10
There was an issue with UMAP install due to a missing comma in the setup.py file, this has been fixed. An optional `min_count` parameter has been added, the default is still 50. All words with total frequency lower `min_count` are ignored by the model.