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    Models/Image Segmentation/tomascanivari/mask2former-swin-large-coco-instance-finetuned-buildings
    Image Segmentationtransformers

    mask2former-swin-large-coco-instance-finetuned-buildings

    by tomascanivari

    Identifier
    Model ID
    tomascanivari/mask2former-swin-large-coco-instance-finetuned-buildings

    Tags

    transformerssafetensorsmask2formerinstance-segmentationimage-segmentationdataset:tomascanivari/buildings-extraction-coco-hfbase_model:facebook/mask2former-swin-large-coco-instancebase_model:finetune:facebook/mask2former-swin-large-coco-instanceendpoints_compatibleregion:us

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    How It Runs on Mixpeek

    On Mixpeek, mask2former-swin-large-coco-instance-finetuned-buildings runs as a managed extractor inside a processing pipeline. Point a bucket of image segmentation 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.