center-for-curriculum-redesign/bge_1-5_query_embeddings
Generate query embeddings from short English text for passage retrieval and semantic search. Accepts an array of query s...
Found 8 models (showing 1-8)
Generate query embeddings from short English text for passage retrieval and semantic search. Accepts an array of query s...
Generate instruction-tuned text embeddings for documents and queries, with an optional relevance score for queryβdocumen...
Reranks pairs of text queries and documents based on their relevance scores using the BGE reranker large model. Takes JS...
Ranks and scores query-document pairs using BAAI's newest balance-striking reranker model. Takes JSON input containing q...
Generate multilingual text similarity scores for retrieval by encoding two newline-separated lists of texts and returnin...
Reranks query-document pairs by computing relevance scores between questions and answers. Takes JSON input containing tu...
Convert text into vector embeddings for semantic search, retrieval-augmented generation, clustering, and classification....
Rerank search results by scoring and ordering documents based on their relevance to a query using the Qwen3 reranker 8B...