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    Models/Visual Question Answering/DAMO-NLP-SG/VideoLLaMA2.1-7B-16F-Base
    Visual Question Answeringtransformersapache-2.0

    VideoLLaMA2.1-7B-16F-Base

    by DAMO-NLP-SG

    Identifier
    Model ID
    DAMO-NLP-SG/VideoLLaMA2.1-7B-16F-Base

    Tags

    transformersvideollama2_qwen2text-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 VideoLLaMA2.1-7B-16F-Base 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, VideoLLaMA2.1-7B-16F-Base 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.