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    Models/Text To Speech/nvidia/magpie_tts_multilingual_357m

    magpie_tts_multilingual_357m

    by nvidia

    Identifier
    Model ID
    nvidia/magpie_tts_multilingual_357m

    Tags

    nemoggufNeMoTTSPyTorchSpeechMultilingual-TTStext-to-speechardeenesfrhiitjakoptvizhdataset:MBZUAI/ClArTTSdataset:tunis-ai/arabic_speech_corpusdataset:mrfakename/Emilia-YODASdataset:MushanW/GLOBE_V2dataset:nvidia/hifitts-2dataset:ai4bharat/Kathbathdataset:joujiboi/japanese-anime-speechdataset:OpenSpeechHub/Common-Voice-17-Jadataset:amphion/Emilia-Datasetdataset:seastar105/Emilia-YODAS-KO-filtered

    Use magpie_tts_multilingual_357m on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, magpie_tts_multilingual_357m runs as a managed extractor inside a processing pipeline. Point a bucket of text to speech 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.