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    Models/Video Classification/KoreaPeter/ms-eff-gcvit-deepfake-b0-kodf
    Video Classificationtransformersmit

    ms-eff-gcvit-deepfake-b0-kodf

    by KoreaPeter

    Identifier
    Model ID
    KoreaPeter/ms-eff-gcvit-deepfake-b0-kodf

    Tags

    transformerssafetensorsms_eff_gcvitimage-classificationPyTorchvisiondeepfake-detectionDeepGuardtf-efficientnetglobal-context-vision-transformervideo-classificationcustom_codedataset:ILSVRC/imagenet-1kbase_model:timm/tf_efficientnet_b0.ns_jft_in1kbase_model:finetune:timm/tf_efficientnet_b0.ns_jft_in1klicense:mitregion:us

    Use ms-eff-gcvit-deepfake-b0-kodf 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, ms-eff-gcvit-deepfake-b0-kodf runs as a managed extractor inside a processing pipeline. Point a bucket of video classification 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.