The Excellence
Directory Platform Template

OpenAI's improved embedding model with 1536 dimensions offering 5x price reduction compared to ada-002, supporting Matryoshka Representation Learning for flexible dimension sizing.

OpenAI's multimodal neural network trained on 400 million image-text pairs, enabling zero-shot image classification and cross-modal retrieval by learning joint embeddings for images and text.

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.

A collection of examples and guides from OpenAI, including best practices for working with embeddings, which are fundamental to vector search and vector database applications.

An embedding function that utilizes the OpenAI API to compute vector embeddings, commonly used with vector databases.

A pre-trained model used for extracting embeddings from content like PDFs, videos, and transcripts, which are then stored in vector databases for faster search.