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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
    16
  • API Endpoint
    3
  • Retrieval Augmented Generation
    9
  • Text-to-Embedding
    6
  • Object Detection
    4
  • Optical Character Recognition
    2
  • Code Generation
    0
  • NVIDIA
    17
  • Baidu
    1
  • University at Buffalo
    1
  • Meta
    0
  • Mistral AI
    0
  • nemo retriever
    • 19 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
    nemoretriever-page-elements-v3
    Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
    Object Detection
    2mo
    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
    nemoretriever-ocr-v1
    Powerful OCR model for fast, accurate real-world image text extraction, layout, and structure analysis.
    Optical Character Recognition
    6mo
    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
    nemoretriever-ocr
    Powerful OCR model for fast, accurate real-world image text extraction, layout, and structure analysis.
    Optical Character Recognition
    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
    nemoretriever-table-structure-v1
    Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
    Object Detection
    11mo
    NVIDIA
    nemoretriever-graphic-elements-v1
    Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
    Object Detection
    11mo
    NVIDIA
    nemoretriever-page-elements-v2
    Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
    Object Detection
    11mo
    NVIDIA
    nemoretriever-parse
    Cutting-edge vision-language model exceling in retrieving text and metadata from images.
    optical character recognition
    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
    University at Buffalo
    cached
    Context-aware chart extraction that can detect 18 classes for chart basic elements, excluding plot elements.
    nemo retriever
    1y
    NVIDIA
    nv-yolox-page-elements-v1
    Model for object detection, fine-tuned to detect charts, tables, and titles in documents.
    Object Detection
    7mo
    Baidu
    paddleocr
    Model for table extraction that receives an image as input, runs OCR on the image, and returns the text within the image and its bounding boxes.
    Optical Character Recognition
    7mo
    NVIDIA
    nv-embedqa-e5-v5
    English text embedding model for question-answering retrieval.
    Embedding
    7mo
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