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    Models/Object Detection/0jung/furniture_use_data_finetuning
    Object Detectiontransformersapache-2.0

    furniture_use_data_finetuning

    by 0jung

    Identifier
    Model ID
    0jung/furniture_use_data_finetuning

    Tags

    transformerspytorchdetrobject-detectiongenerated_from_trainerbase_model:facebook/detr-resnet-50base_model:finetune:facebook/detr-resnet-50license:apache-2.0endpoints_compatibleregion:us

    Use furniture_use_data_finetuning 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, furniture_use_data_finetuning 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.