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13 results for

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    3
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    6
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    5
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    1
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    Downloadable

    bge-m3

    Embedding model for text retrieval tasks, excelling in dense, multi-vector, and sparse retrieval.
    Model
    Embeddings
    3.36M
    1y

    Use this skill when deploying, operating, or integrating the VSS 3.2 GA RT-Embed Video Embedding microservice. Covers Docker Compose bring-up, GPU and storage prerequisites, the `/v1` REST API (file uploads, text and video embeddings, live RTSP streams, h
    Skill
    Video Search and Summarization (VSS)
    369
    1d
    Items per page
    of 1 pages
    Meta
    Free Endpoint

    esm2-650m

    Generates embeddings of proteins from their amino acid sequences.
    Model
    nim
    128K
    1y
    NVIDIA
    Free Endpoint

    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.
    Model
    nemo retriever
    1.38M
    1y
    Financial Services
    LaunchableDeveloper Example

    Build Your Own Transaction Foundation Model

    Create intelligent embeddings by using transformer architecture on tabular data.
    Blueprint
    NVIDIA AI
    2mo
    NVIDIA
    Free Endpoint

    nv-embed-v1

    Generates high-quality numerical embeddings from text inputs.
    Model
    Non-Commercial Use Only
    3.83M
    10mo
    NVIDIA
    Downloadable

    llama-nemotron-embed-vl-1b-v2

    Multimodal question-answer retrieval representing user queries as text and documents as images.
    Model
    nemo retriever
    7.59M
    4mo
    NVIDIA
    Downloadable

    nv-embedqa-e5-v5

    English text embedding model for question-answering retrieval.
    Model
    Embedding
    16.12M
    10mo

    CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, or deploying CL
    Skill
    AI Engineer
    178
    1d

    Metric-learning recognition (ml-recog) for fine-grained visual recognition. Learns embeddings for retrieval-based matching (e.g., retail product recognition) using triplet / contrastive losses. Use when training, evaluating, exporting, or running inferenc
    Skill
    Developer
    178
    1d

    Person re-identification (ReID). Learns discriminative embeddings to match the same person across different camera views, based on metric learning. Use when training, evaluating, exporting, or running inference for a TAO person re-identification model. Tr
    Skill
    Developer
    176
    1d

    LP, MILP, and QP (beta) with cuOpt — C API only. Use when the user is embedding LP, MILP, or QP in C/C++.
    Skill
    Developer
    469
    15d
    NVIDIA
    Downloadable

    llama-nemotron-embed-1b-v2

    Multilingual, cross-lingual embedding model for long-document QA retrieval, supporting 26 languages.
    Model
    Text-to-Embedding
    4.45M
    3mo