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    Models/Automatic Speech Recognition/eddiegulay/wav2vec2-large-xlsr-mvc-swahili
    Automatic Speech Recognitiontransformersapache-2.0

    wav2vec2-large-xlsr-mvc-swahili

    by eddiegulay

    408Kdl/month
    3likes
    Identifier
    Model ID
    eddiegulay/wav2vec2-large-xlsr-mvc-swahili

    Tags

    transformerstensorboardsafetensorswav2vec2automatic-speech-recognitiongenerated_from_trainerswdataset:common_voice_13_0base_model:facebook/wav2vec2-large-xlsr-53base_model:finetune:facebook/wav2vec2-large-xlsr-53license:apache-2.0model-indexendpoints_compatibleregion:us

    Use wav2vec2-large-xlsr-mvc-swahili 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-mvc-swahili 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.