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    Models/Document Question Answering/guo1006/layoutlmv2-base-uncased-finetuned-docvqa_1200_examples

    layoutlmv2-base-uncased-finetuned-docvqa_1200_examples

    by guo1006

    Identifier
    Model ID
    guo1006/layoutlmv2-base-uncased-finetuned-docvqa_1200_examples

    Tags

    transformerssafetensorslayoutlmv2document-question-answeringgenerated_from_trainerendpoints_compatibleregion:us

    Use layoutlmv2-base-uncased-finetuned-docvqa_1200_examples 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, layoutlmv2-base-uncased-finetuned-docvqa_1200_examples runs as a managed extractor inside a processing pipeline. Point a bucket of document 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.