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Models

Deploy and scale models on your GPU infrastructure of choice with NVIDIA NIM inference microservices

Optimized by NVIDIALaunch from Hugging FaceBeta

Filters (1)

  • Download Available
    8
  • API Endpoint
    4
  • Retrieval Augmented Generation
    12
  • Text-to-Embedding
    8
  • Code Generation
    0
  • Drug Discovery
    0
  • Image-to-Text
    0
  • NVIDIA
    11
  • BAAI
    1
  • Meta
    0
  • Mistral AI
    0
  • Microsoft
    0
  • Retrieval Augmented Generation
    • 12 models
    NVIDIA
    llama-nemotron-embed-vl-1b-v2
    Multimodal question-answer retrieval representing user queries as text and documents as images.
    nemo retriever
    3w
    NVIDIA
    llama-3_2-nemoretriever-300m-embed-v2
    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Retrieval Augmented Generation
    5mo
    NVIDIA
    llama-3_2-nemoretriever-300m-embed-v1
    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Retrieval Augmented Generation
    7mo
    NVIDIA
    llama-3.2-nemoretriever-500m-rerank-v2
    GPU-accelerated model optimized for providing a probability score that a given passage contains the information to answer a question.
    nemo retriever
    8mo
    NVIDIA
    llama-3.2-nemoretriever-1b-vlm-embed-v1
    Multimodal question-answer retrieval representing user queries as text and documents as images.
    nemo retriever
    8mo
    NVIDIA
    nv-embedcode-7b-v1
    The NV-EmbedCode model is a 7B Mistral-based embedding model optimized for code retrieval, supporting text, code, and hybrid queries.
    nemo retriever
    9mo
    NVIDIA
    llama-3.2-nv-embedqa-1b-v2
    Multilingual and cross-lingual text question-answering retrieval with long context support and optimized data storage efficiency.
    nemo retriever
    7mo
    NVIDIA
    llama-3.2-nv-rerankqa-1b-v2
    Fine-tuned reranking model for multilingual, cross-lingual text question-answering retrieval, with long context support.
    nemo retriever
    7mo
    NVIDIA
    nv-embedqa-e5-v5
    English text embedding model for question-answering retrieval.
    Embedding
    7mo
    NVIDIA
    nv-embed-v1
    Generates high-quality numerical embeddings from text inputs.
    Non-Commercial Use Only
    7mo
    BAAI
    bge-m3
    Embedding model for text retrieval tasks, excelling in dense, multi-vector, and sparse retrieval.
    Embeddings
    10mo
    NVIDIA
    rerank-qa-mistral-4b
    GPU-accelerated model optimized for providing a probability score that a given passage contains the information to answer a question.
    Ranking
    1y
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