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    Models/Visual Question Answering/DAMO-NLP-SG/VideoLLaMA3-7B-Image
    Visual Question Answeringtransformersapache-2.0

    VideoLLaMA3-7B-Image

    by DAMO-NLP-SG

    Identifier
    Model ID
    DAMO-NLP-SG/VideoLLaMA3-7B-Image

    Tags

    transformerssafetensorsvideollama3_qwen2text-generationmulti-modallarge-language-modelvideo-language-modelvisual-question-answeringcustom_codeendataset:lmms-lab/LLaVA-OneVision-Datadataset:allenai/pixmo-docsdataset:HuggingFaceM4/Docmatixdataset:lmms-lab/LLaVA-Video-178Kdataset:ShareGPT4Video/ShareGPT4Videoarxiv:2501.13106arxiv:2406.07476arxiv:2306.02858base_model:Qwen/Qwen2.5-7B-Instructbase_model:finetune:Qwen/Qwen2.5-7B-Instructlicense:apache-2.0region:us

    Use VideoLLaMA3-7B-Image 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, VideoLLaMA3-7B-Image 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.