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    Models/Audio Classification/abhishtagatya/hubert-base-960h-asv19-deepfake
    Audio Classificationtransformersapache-2.0

    hubert-base-960h-asv19-deepfake

    by abhishtagatya

    Identifier
    Model ID
    abhishtagatya/hubert-base-960h-asv19-deepfake

    Tags

    transformerstensorboardsafetensorshubertaudio-classificationdeepfakeaudio-spoofgenerated_from_trainerbase_model:facebook/hubert-base-ls960base_model:finetune:facebook/hubert-base-ls960license:apache-2.0endpoints_compatibleregion:us

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    How It Runs on Mixpeek

    On Mixpeek, hubert-base-960h-asv19-deepfake runs as a managed extractor inside a processing pipeline. Point a bucket of audio 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.