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    Models/Audio Classification/ThomasR/facebook_wav2vec2-large_October_03_2023_05h34PM
    Audio Classificationtransformersapache-2.0

    facebook_wav2vec2-large_October_03_2023_05h34PM

    by ThomasR

    Identifier
    Model ID
    ThomasR/facebook_wav2vec2-large_October_03_2023_05h34PM

    Tags

    transformerspytorchwav2vec2audio-classificationgenerated_from_trainerdataset:audiofolderbase_model:facebook/wav2vec2-largebase_model:finetune:facebook/wav2vec2-largelicense:apache-2.0model-indexendpoints_compatibleregion:us

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    How It Runs on Mixpeek

    On Mixpeek, facebook_wav2vec2-large_October_03_2023_05h34PM 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.