E5-base-v2

E5-base-v2 is an open-weight English text embedding model from intfloat that encodes sentences and passages into 768-dimensional vectors for semantic search, document retrieval, similarity scoring, and clustering. It uses a 12-layer transformer architecture and is optimized for retrieval tasks on English-only inputs up to 512 tokens. Source: supabase.