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 query–documen...
Rerank text passages for a query by scoring text pairs and returning relevance scores. Accept a JSON list of (query, doc...
Rerank query–document pairs for information retrieval and RAG. Accepts text inputs as one or many [query, passage] pairs...
Generate multilingual text similarity scores for retrieval by encoding two newline-separated lists of texts and returnin...
Re-rank query–candidate text pairs for search and RAG by returning a relevance score per pair. Takes a JSON-encoded list...
Convert text into vector embeddings for semantic search, retrieval-augmented generation, clustering, and classification....
Rank documents by relevance to a text query. Accepts a query and a list of documents (JSON string) with an optional inst...