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    Models/Video Classification/Shawon16/ViViT_WLASL_100_SR_4_ep200_p20
    Video Classificationtransformersmit

    ViViT_WLASL_100_SR_4_ep200_p20

    by Shawon16

    Identifier
    Model ID
    Shawon16/ViViT_WLASL_100_SR_4_ep200_p20

    Deploy ViViT_WLASL_100_SR_4_ep200_p20

    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

    transformerssafetensorsvivitvideo-classificationgenerated_from_trainerbase_model:google/vivit-b-16x2-kinetics400base_model:finetune:google/vivit-b-16x2-kinetics400license:mitendpoints_compatibleregion:us

    Use ViViT_WLASL_100_SR_4_ep200_p20 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, ViViT_WLASL_100_SR_4_ep200_p20 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.