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

Reranks documents based on their relevance to a search query. Takes a query string and a list of documents as input, the...

text-embedding • document-ranking • 27 runs

🤖 Model

sesamo-srl/bge-reranker-v2-m3

Reranks query-document pairs by computing relevance scores between questions and answers. Takes JSON input containing tu...

text-embedding • 371.0K 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

Reranks pairs of text queries and documents based on their relevance scores using the BGE reranker large model. Takes JS...

📝 → 📝 • text-embedding • text-generation • 25 runs

🤖 Model

yxzwayne/bge-reranker-v2-gemma

Calculates relevance and similarity scores between text pairs. Takes JSON-formatted input containing query-passage pairs...

text-embedding • 124 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

Ranks and scores query-document pairs using BAAI's newest balance-striking reranker model. Takes JSON input containing q...

text-embedding • document-ranking • information-retrieval • 64.1K 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 • 15 runs