World-class multilingual and cross-lingual question-answering retrieval.

Generates embeddings of proteins from their amino acid sequences.

NV-DINOv2 is a visual foundation model that generates vector embeddings for the input image.

NV-CLIP is a multimodal embeddings model for image and text.

Generates high-quality numerical embeddings from text inputs.

Embedding model for text retrieval tasks, excelling in dense, multi-vector, and sparse retrieval.

GPU-accelerated generation of text embeddings used for question-answering retrieval.