rag AI Models

🤖 Model

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...

text-embedding • semantic-search • sentence-similarity • 7.6K runs

🤖 Model

yxzwayne/jina-reranker-v1-turbo-en

Rerank documents for a text query, returning the top-k most relevant texts with relevance scores. Accepts a text query a...

reranking • semantic-search • rag • 21 runs

🤖 Model

sesamo-srl/bge-reranker-v2-m3

Re-rank query–candidate text pairs for search and RAG by returning a relevance score per pair. Takes a JSON-encoded list...

text-reranking • information-retrieval • rag • 91.8K runs

🤖 Model 📝 → 📝

tomasmcm/docsgpt-7b-mistral

Generates context-based answers from textual prompts, optimized for documentation retrieval and question answering. Fine...

📝 → 📝 • text-generation • question-answering • documentation • 78 runs

🤖 Model

fakturi/bge-reranker-large

Rerank text passages for a query by scoring text pairs and returning relevance scores. Accept a JSON list of (query, doc...

text-reranking • information-retrieval • retrieval-augmented-generation • 25 runs

🤖 Model

yxzwayne/bge-reranker-v2-gemma

Score relevance between queries and passages for retrieval re-ranking. Accept a JSON string containing one or many [quer...

reranking • semantic-search • text-similarity • 115 runs

🤖 Model

adirik/e5-mistral-7b-instruct

Generate instruction-tuned text embeddings for documents and queries, with an optional relevance score for query–documen...

text-embedding • 649 runs

🤖 Model

cuuupid/gte-qwen2-7b-instruct

Convert text into dense vector embeddings for semantic search and retrieval. Generate sentence and paragraph embeddings...

text-embedding • semantic-search • retrieval-augmented-generation • 1.1M runs

🤖 Model

yxzwayne/bge-reranker-v2-m3

Rerank query–document pairs for information retrieval and RAG. Accepts text inputs as one or many [query, passage] pairs...

text-reranking • information-retrieval • rag • 63.2K runs

🤖 Model

lucataco/snowflake-arctic-embed-l

Embed text into 1024-dimensional vectors for semantic search, dense retrieval, and RAG pipelines. Takes a text prompt an...

text-embedding • 398.5K runs

🤖 Model

lucataco/nomic-embed-text-v1

Convert text into vector embeddings for semantic search, retrieval-augmented generation, clustering, and classification....

text-embedding • semantic-search • rag • 34.3K runs

🤖 Model

yorickvp/jina-embeddings-v2-base-en

Convert English text into vector embeddings for semantic search, long-document retrieval, reranking, recommendation, and...

text-embedding • semantic-search • rag • 51 runs

🤖 Model 📝 → 📝

light770/qwen3-reranker-0.6b

Reranks search results by scoring query-document pairs for improved retrieval accuracy in RAG pipelines. Uses a cross-en...

📝 → 📝 • text-embedding • text-generation • 13 runs