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    Models/Object Detection/nsugianto/tblstructrecog_finetuned_tbltransstrucrecog_v1_s1_394s_adjpar6_lr1e6_dec1e5_bs4
    Object Detectiontransformersmit

    tblstructrecog_finetuned_tbltransstrucrecog_v1_s1_394s_adjpar6_lr1e6_dec1e5_bs4

    by nsugianto

    Identifier
    Model ID
    nsugianto/tblstructrecog_finetuned_tbltransstrucrecog_v1_s1_394s_adjpar6_lr1e6_dec1e5_bs4

    Tags

    transformerstensorboardsafetensorstable-transformerobject-detectiongenerated_from_trainerbase_model:microsoft/table-transformer-structure-recognitionbase_model:finetune:microsoft/table-transformer-structure-recognitionlicense:mitendpoints_compatibleregion:us

    Use tblstructrecog_finetuned_tbltransstrucrecog_v1_s1_394s_adjpar6_lr1e6_dec1e5_bs4 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, tblstructrecog_finetuned_tbltransstrucrecog_v1_s1_394s_adjpar6_lr1e6_dec1e5_bs4 runs as a managed extractor inside a processing pipeline. Point a bucket of object detection 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.