BERTopic

BERTopic is a topic modeling technique that leverages transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions.

BERTopic is popular for its modularity, which means we can use any desired algorithm inside it:

Example

from bertopic import BERTopic

topic_model = BERTopic(
    embedding_model=embedding_model,
    umap_model=umap_model,
    hdbscan_model=hdbscan_model,
    verbose=True
).fit(abstracts, embeddings)