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    Models/Audio Classification/Bisher/wav2vec2_ASV_deepfake_audio_detection
    Audio Classificationtransformersapache-2.0

    wav2vec2_ASV_deepfake_audio_detection

    by Bisher

    Identifier
    Model ID
    Bisher/wav2vec2_ASV_deepfake_audio_detection

    Tags

    transformerstensorboardsafetensorswav2vec2audio-classificationgenerated_from_trainerbase_model:facebook/wav2vec2-basebase_model:finetune:facebook/wav2vec2-baselicense:apache-2.0endpoints_compatibleregion:us

    Use wav2vec2_ASV_deepfake_audio_detection on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

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    How It Runs on Mixpeek

    On Mixpeek, wav2vec2_ASV_deepfake_audio_detection 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.