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nvidia/llama-3.2-nv-embedqa-1b-v1
World-class multilingual and cross-lingual question-answering retrieval.
meta/esm2-650m
Generates embeddings of proteins from their amino acid sequences.
nvidia/nv-dinov2
NV-DINOv2 is a visual foundation model that generates vector embeddings for the input image.
nvidia/nv-embedqa-e5-v5
GPU-accelerated generation of text embeddings used for question-answering retrieval.
nvidia/nv-embedqa-mistral-7b-v2
GPU-accelerated generation of text embeddings used for question-answering retrieval.
nvidia/nvclip
NV-CLIP is a multimodal embeddings model for image and text.
nvidia/nv-embed-v1
Generates high-quality numerical embeddings from text inputs.
baai/bge-m3
Embedding model for text retrieval tasks, excelling in dense, multi-vector, and sparse retrieval.
snowflake/arctic-embed-l
GPU-accelerated generation of text embeddings.
nvidia/embed-qa-4
GPU-accelerated generation of text embeddings used for question-answering retrieval.