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    Models/Video Classification/Shawon16/VideoMAE_base_wlasl_100__signer_200ep_coR
    Video Classificationtransformerscc-by-nc-4.0

    VideoMAE_base_wlasl_100__signer_200ep_coR

    by Shawon16

    Identifier
    Model ID
    Shawon16/VideoMAE_base_wlasl_100__signer_200ep_coR

    Deploy VideoMAE_base_wlasl_100__signer_200ep_coR

    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

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

    Use VideoMAE_base_wlasl_100__signer_200ep_coR 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, VideoMAE_base_wlasl_100__signer_200ep_coR 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.