
lucataco/nomic-embed-text-v1
Convert text into vector embeddings for semantic search, retrieval, clustering, and classification. Accept a newline-sep...
Found 41 models (showing 1-20)
Convert text into vector embeddings for semantic search, retrieval, clustering, and classification. Accept a newline-sep...
Convert text into 1024-dimensional embeddings for semantic search and retrieval. Takes a text prompt and returns a dense...
Generate joint text and image embeddings for semantic search and cross‑modal retrieval. Accepts a single text string or...
Convert text into dense vector embeddings for semantic search, retrieval, clustering, and classification. Accepts single...
Convert multilingual text into dense embeddings for semantic search and cross-lingual retrieval. Accepts a list of texts...
Convert text to vector embeddings for semantic search, retrieval, clustering, and RAG. Accepts an array of texts and ret...
Embed text, images, and audio into a shared vector space for cross-modal retrieval and similarity search. Accepts a text...
Generate dense embeddings for document screenshots and text queries to power document and webpage retrieval. Encode scre...
Convert text into 128–768-dimensional embeddings for semantic search, retrieval, and clustering. Accepts text input (up...
Convert text into embeddings for semantic search and retrieval. Takes a text string and returns a 768-dimensional embedd...
Convert English text into dense vector embeddings for semantic search and retrieval. Accept batches of texts and return...
Generate text query embeddings for dense retrieval and semantic search. Accepts an array of short query strings and retu...
Generate text embeddings from one or more text inputs. Accepts up to five separate strings and returns a dense embedding...
Convert text into multilingual embeddings for semantic search and retrieval. Accepts a list of texts and returns a 768-d...
Generate text and image embeddings. Produce 768-dimensional vectors from text or images using CLIP ViT-L/14 for semantic...
Compute CLIP ViT-L/14 embeddings from text and images for semantic search, cross-modal retrieval, and zero-shot classifi...
Compute 512-dimensional embeddings from images and/or text for similarity search, cross‑modal retrieval, clustering, ded...
Create multilingual text and image embeddings for cross-modal search, retrieval, and similarity. Accept text (up to 8192...
Convert text into embeddings for semantic search and retrieval. Accepts a document string and optionally a query and a o...
Compute semantic relevance between a query and a passage and generate multilingual text embeddings. Takes a text query a...