HuggingFace Text Embedding Server

High-performance multilingual embedding model from Cohere supporting 100+ languages with 1024 dimensions, optimized for semantic search, RAG, and cross-lingual retrieval tasks.

State-of-the-art embedding model from Mistral AI that generates 1024-dimensional vectors for text, supporting semantic search, clustering, and retrieval-augmented generation applications.

AI startup providing state-of-the-art embedding and reranking models through accessible APIs, offering both open-source and proprietary models optimized for various use cases.

OpenAI's flagship text embedding model with up to 3,072 dimensions, offering best-in-class performance and accuracy for English tasks with adjustable output sizes to optimize storage costs.

An embedding function implementation within the ChromaDB Java client (tech.amikos.chromadb.embeddings.hf.HuggingFaceEmbeddingFunction) that utilizes Hugging Face's cloud-based inference API to generate vector embeddings for documents.

A wrapper embedding function for Jina Embedding models, used to generate vector embeddings.