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    Models/Audio Classification/hanxunh/AudioMosaic-vit-b16-linear-prob-as20k-attentive
    Audio ClassificationAudioMosaicmit

    AudioMosaic-vit-b16-linear-prob-as20k-attentive

    by hanxunh

    Identifier
    Model ID
    hanxunh/AudioMosaic-vit-b16-linear-prob-as20k-attentive

    Tags

    AudioMosaicsafetensorsarxiv:2605.14231audioaudio-classificationaudiosetlinear-probeself-supervised-learningbase_model:hanxunh/AudioMosaic-vit-b16-pretrainedbase_model:finetune:hanxunh/AudioMosaic-vit-b16-pretrainedlicense:mitmodel-indexregion:us

    Use AudioMosaic-vit-b16-linear-prob-as20k-attentive 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, AudioMosaic-vit-b16-linear-prob-as20k-attentive 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.