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    Models/Visual Question Answering/DAMO-NLP-SG/VideoLLaMA2-8x7B
    Visual Question Answeringtransformersapache-2.0

    VideoLLaMA2-8x7B

    by DAMO-NLP-SG

    Identifier
    Model ID
    DAMO-NLP-SG/VideoLLaMA2-8x7B

    Tags

    transformerssafetensorsvideollama2_mixtraltext-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 VideoLLaMA2-8x7B on Mixpeek

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

    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, VideoLLaMA2-8x7B 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.