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    Models/Image Segmentation/sumeyya/segformer-b0-finetuned-Eduardo-food103-GOOGLE100
    Image Segmentationtransformersother

    segformer-b0-finetuned-Eduardo-food103-GOOGLE100

    by sumeyya

    Identifier
    Model ID
    sumeyya/segformer-b0-finetuned-Eduardo-food103-GOOGLE100

    Deploy segformer-b0-finetuned-Eduardo-food103-GOOGLE100

    Single-tenant

    Mixpeek has no managed extractor for this model. On a single-tenant deployment you upload the weights and a custom plugin serves them next to the rest of your pipeline.

    Tags

    transformerstensorboardsafetensorssegformervisionimage-segmentationgenerated_from_trainerbase_model:nvidia/mit-b0base_model:finetune:nvidia/mit-b0license:otherendpoints_compatibleregion:us

    Use segformer-b0-finetuned-Eduardo-food103-GOOGLE100 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, segformer-b0-finetuned-Eduardo-food103-GOOGLE100 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.