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    Models/Table Question Answering/google/tapas-large-finetuned-wtq
    Table Question Answeringtransformersapache-2.0

    tapas-large-finetuned-wtq

    by google

    35Kdl/month
    148likes
    Identifier
    Model ID
    google/tapas-large-finetuned-wtq

    Tags

    transformerspytorchtfsafetensorstapastable-question-answeringendataset:wikitablequestionsarxiv:2004.02349arxiv:2010.00571arxiv:1508.00305license:apache-2.0endpoints_compatibledeploy:azureregion:us

    Use tapas-large-finetuned-wtq 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, tapas-large-finetuned-wtq runs as a managed extractor inside a processing pipeline. Point a bucket of table 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.