gensim version fix

Fixes #152

1.0.23

Added numpy>=1.20.0 dependency.

1.0.22

Numpy related bug fix and document id validation performance upgrade.

added umap/hdbscan custom args

Addressed #90, #125, #126

Added custom umap and hdbscan arg option. Fixed issue with loading model with custom tokenizer.

added use_embedding_model_tokenizer option

Added use_embedding_model_tokenizer parameter. If set to True and if using an embedding_model other than doc2vec, use the model's tokenizer for document embedding.

Fixed dependency issue with joblib.

Fixed issues with wordclouds caused by negative similarity scores.

fix saving bug

Fixed bug #91

word indexing

Added option for indexing word vectors, this will speed up search for models with large vocabularies. Specifically search_words_by_vector and similar_words.

Added new method search_words_by_vector.

document indexing

Added option for indexing document vectors, this will speed up search for models with large number of documents. Specifically search_documents_by_vector, search_documents_by_keywords, and search_documents_by_documents.

Added new method search_documents_by_vector.

Added code to prevent hierarchical topic reduction error #79.

Separate dependencies

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.

logging bug fix and default change

The verbose parameter will be set to True by default.

Fixed a bug that stopped showing logging updates after downloading pre-trained models.