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    Models/Video Classification/mayarmostafa/videomae-base-finetuned-bleeding_5fs3s_weights_lr1e-4_warmup0.1_1
    Video Classificationtransformerscc-by-nc-4.0

    videomae-base-finetuned-bleeding_5fs3s_weights_lr1e-4_warmup0.1_1

    by mayarmostafa

    Identifier
    Model ID
    mayarmostafa/videomae-base-finetuned-bleeding_5fs3s_weights_lr1e-4_warmup0.1_1

    Deploy videomae-base-finetuned-bleeding_5fs3s_weights_lr1e-4_warmup0.1_1

    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

    transformerstensorboardsafetensorsvideomaevideo-classificationgenerated_from_trainerbase_model:MCG-NJU/videomae-basebase_model:finetune:MCG-NJU/videomae-baselicense:cc-by-nc-4.0endpoints_compatibleregion:us

    Use videomae-base-finetuned-bleeding_5fs3s_weights_lr1e-4_warmup0.1_1 on Mixpeek

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    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, videomae-base-finetuned-bleeding_5fs3s_weights_lr1e-4_warmup0.1_1 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.