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    Models/Object Detection/nsugianto/detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6
    Object Detectiontransformers

    detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6

    by nsugianto

    Identifier
    Model ID
    nsugianto/detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6

    Tags

    transformerstensorboardsafetensorsdetrobject-detectiongenerated_from_trainerbase_model:nsugianto/detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6base_model:finetune:nsugianto/detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6endpoints_compatibleregion:us

    Use detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6 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, detr-resnet50_finetuned_lstabledetv1s9_lsdocelementdetv1type3_session6 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.