
center-for-curriculum-redesign/bge_1-5_query_embeddings
Generate text query embeddings for dense retrieval and semantic search. Accepts an array of short query strings and retu...
Found 6 models (showing 1-6)
Generate text query embeddings for dense retrieval and semantic search. Accepts an array of short query strings and retu...
Convert text into embeddings for semantic search and retrieval. Accepts a document string and optionally a query and a o...
Re-rank documents and passages for retrieval using query–document pairs, returning relevance scores for each pair. Accep...
Rerank passages for a text query. Takes a query and one or more candidate documents (text) and outputs a relevance score...
Compute pairwise text similarity for retrieval. Accepts two newline-separated lists of texts and an embedding mode (dens...
Score relevance between text pairs for reranking search results and retrieval-augmented generation. Takes a JSON list of...