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    Models/Automatic Speech Recognition/efficient-speech/lite-whisper-large-v3-turbo-acc
    Automatic Speech Recognitiontransformersapache-2.0

    lite-whisper-large-v3-turbo-acc

    by efficient-speech

    Identifier
    Model ID
    efficient-speech/lite-whisper-large-v3-turbo-acc

    Tags

    transformerssafetensorslite-whisperimage-feature-extractionaudioautomatic-speech-recognitionwhisperhf-asr-leaderboardcustom_codearxiv:2502.20583base_model:openai/whisper-large-v3-turbobase_model:finetune:openai/whisper-large-v3-turbolicense:apache-2.0eval-resultsregion:us

    Use lite-whisper-large-v3-turbo-acc 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, lite-whisper-large-v3-turbo-acc 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.