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    Models/Automatic Speech Recognition/jonatasgrosman/wav2vec2-large-xlsr-53-english
    Automatic Speech Recognitiontransformersapache-2.0

    wav2vec2-large-xlsr-53-english

    by jonatasgrosman

    55Kdl/month
    477likes
    Identifier
    Model ID
    jonatasgrosman/wav2vec2-large-xlsr-53-english

    Tags

    transformerspytorchjaxsafetensorswav2vec2automatic-speech-recognitionaudioenhf-asr-leaderboardmozilla-foundation/common_voice_6_0robust-speech-eventspeechxlsr-fine-tuning-weekdataset:common_voicedataset:mozilla-foundation/common_voice_6_0doi:10.57967/hf/3569license:apache-2.0model-indexendpoints_compatibleregion:us

    Use wav2vec2-large-xlsr-53-english 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-large-xlsr-53-english runs as a managed extractor inside a processing pipeline. Point a bucket of automatic speech recognition 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.