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    Models/Automatic Speech Recognition/optimum-intel-internal-testing/sew-d-tiny-100k-ft-ls100h

    sew-d-tiny-100k-ft-ls100h

    by optimum-intel-internal-testing

    Identifier
    Model ID
    optimum-intel-internal-testing/sew-d-tiny-100k-ft-ls100h

    Tags

    pytorchsafetensorssew-daudiospeechautomatic-speech-recognitionhf-asr-leaderboardendataset:librispeech_asrarxiv:2109.06870license:apache-2.0model-indexregion:us

    Use sew-d-tiny-100k-ft-ls100h 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, sew-d-tiny-100k-ft-ls100h 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.