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    Models/Document Question Answering/zibajoon/20231101_layoutlm2_1.2k_3ep_Doc_A
    Document Question Answeringtransformerscc-by-nc-sa-4.0

    20231101_layoutlm2_1.2k_3ep_Doc_A

    by zibajoon

    Identifier
    Model ID
    zibajoon/20231101_layoutlm2_1.2k_3ep_Doc_A

    Deploy 20231101_layoutlm2_1.2k_3ep_Doc_A

    Single-tenant

    Mixpeek has no managed extractor for this model. On a single-tenant deployment you upload the weights and a custom plugin serves them next to the rest of your pipeline.

    Tags

    transformerspytorchlayoutlmv2document-question-answeringgenerated_from_trainerbase_model:microsoft/layoutlmv2-base-uncasedbase_model:finetune:microsoft/layoutlmv2-base-uncasedlicense:cc-by-nc-sa-4.0endpoints_compatibleregion:us

    Use 20231101_layoutlm2_1.2k_3ep_Doc_A 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, 20231101_layoutlm2_1.2k_3ep_Doc_A 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.