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    Models/Visual Question Answering/CHELSEA234/llava-v1.5-7b-M2F2-Det

    llava-v1.5-7b-M2F2-Det

    by CHELSEA234

    Identifier
    Model ID
    CHELSEA234/llava-v1.5-7b-M2F2-Det

    Tags

    safetensorsllava_llamavisual-question-answeringenarxiv:2402.00126arxiv:2410.02761base_model:meta-llama/Llama-2-7b-hfbase_model:finetune:meta-llama/Llama-2-7b-hflicense:mitregion:us

    Use llava-v1.5-7b-M2F2-Det 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, llava-v1.5-7b-M2F2-Det 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.