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    Models/Visual Question Answering/DAMO-NLP-SG/VideoLLaMA2-7B
    Visual Question Answeringtransformersapache-2.0

    VideoLLaMA2-7B

    by DAMO-NLP-SG

    849dl/month
    40likes
    Identifier
    Model ID
    DAMO-NLP-SG/VideoLLaMA2-7B

    Tags

    transformerssafetensorsvideollama2_mistraltext-generationmultimodal large language modellarge video-language modelvisual-question-answeringendataset:OpenGVLab/VideoChat2-ITdataset:Lin-Chen/ShareGPT4Vdataset:liuhaotian/LLaVA-Instruct-150Karxiv:2406.07476arxiv:2306.02858license:apache-2.0endpoints_compatibleregion:us

    Use VideoLLaMA2-7B on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

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    How It Runs on Mixpeek

    On Mixpeek, VideoLLaMA2-7B runs as a managed extractor inside a processing pipeline. Point a bucket of visual question answering data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.