CamemBERT is an advanced French language model based on RoBERTa, offering 6 different versions suitable for various French natural language processing tasks.

Natural Language ProcessingTransformersFrench

This is a multilingual sentence transformer model capable of mapping sentences and paragraphs into a 512-dimensional dense vector space, suitable for tasks such as clustering or semantic search.

Natural Language ProcessingTransformers

This is a multilingual sentence embedding model that maps text to a 384-dimensional vector space, suitable for semantic search and clustering tasks.

Natural Language ProcessingTransformers

This is a sentence transformer model that maps sentences and paragraphs into a 384-dimensional dense vector space, suitable for tasks such as clustering or semantic search.

Natural Language ProcessingTransformers

This is a sentence transformer model based on the ALBERT-small architecture, capable of mapping sentences and paragraphs into a 768-dimensional vector space, suitable for tasks such as sentence similarity calculation and semantic search.

Natural Language ProcessingTransformers