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  • SearchSearch thousands of GPU-optimized Containers, pretrained Models, SDKs, and Helm charts—ready to accelerate AI, digital twins, and HPC from cloud to edge.
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  • Displaying 38 results
    Riva Speech Skills
    NVIDIA
    Riva Speech Skills is a scalable Conversational AI service platform.
    Container
    Riva TTS NIM
    NVIDIA
    RIVA TTS NIM provide easy access to state-of-the-art text to speech models, capable of synthesizing English speech from text
    Container
    Riva Skills Quick Start
    NVIDIA
    Scripts and utilities for getting started with Riva Speech Skills
    Resource
    TTS FastPitch HifiGAN Riva
    NVIDIA
    RIVA TTS NIM provide easy access to state-of-the-art text to speech models, capable of synthesizing English speech from text
    Container
    Chatterbox TTS Multilingual
    Nvidia
    Chatterbox TTS Multilingual NIM Container
    Container
    Magpie TTS Zeroshot NIM
    NVIDIA
    Riva Magpie TTS Zeroshot NIM synthesizes natural sounding speech using voice features from reference speech sample.
    Container
    Riva TTS English US Auxiliary Files
    NVIDIA
    Contains files used in rmir creation
    Model
    WaveGlow LJS 256 Channels
    NVIDIA
    WaveGlow model weights pre-trained on the LJ Speech dataset to be used with https://github.com/NVIDIA/waveglow.
    Model
    HiFi-GAN PyT checkpoint (22kHz, AMP)
    NVIDIA Deep Learning Examples
    HiFi-GAN v1 PyTorch checkpoint trained on 8GPU with AMP on LJSpeech-1.1 (22kHz).
    Model
    nemo-speech.cpp
    NVIDIA
    A lightweight native C++ runtime for NVIDIA Nemotron Speech models built on ggml. Runs speech models in real time and batch mode across platforms and backends.
    Container
    WaveGlow
    NVIDIA
    WaveGlow is a flow-based network capable of generating high quality speech from mel-spectrograms.
    Model
    Text to Speech Notebook
    NVIDIA
    End to End workflow for text to speech training with TAO Toolkit and deployment using Riva.
    Resource
    HiFi-GAN PyT checkpoint (FastPitch ftune, 22kHz, AMP)
    NVIDIA Deep Learning Examples
    HiFi-GAN v1 PyTorch checkpoint trained on 8GPU with AMP on LJSpeech-1.1 (22kHz), fine-tuned on FastPitch outputs.
    Model
    Tacotron2 LJSpeech
    NVIDIA
    Model checkpoints for the Tacotron 2 model trained with NeMo.
    Model
    Speech Synthesis English FastPitch
    NVIDIA
    Mel-Spectrogram prediction conditioned on input text with LJSpeech voice.
    Model
    Speech Synthesis HiFi-GAN
    NVIDIA
    GAN-based waveform generator from mel-spectrograms.
    Model
    Audio Codec 16kHz Small
    NVIDIA
    This model card contains a Small Audio Codec model trained on the Libri-Light audiobook recordings dataset, comprising approximately 60,000 hours of English language speech with a 16kHz sampling rate.
    Model
    WaveGlow LJSpeech
    NVIDIA
    Model checkpoints for the WaveGlow model trained with NeMo.
    Model
    HiFi-GAN for PyTorch
    NVIDIA Deep Learning Examples
    HiFi-GAN model implements a spectrogram inversion model that allows to synthesize speech waveforms from mel-spectrograms.
    Resource
    RIVA Magpie-TTS Multilingual
    NVIDIA
    Riva NeMo-MagpieTTS Multilingual IPA multispeaker model with Emotions
    Model
    Tacotron2 PyTorch checkpoint (AMP)
    NVIDIA Deep Learning Examples
    Tacotron2 PyTorch checkpoint trained with AMP
    Model
    Flowtron
    NVIDIA
    Flowtron is an Autoregressive Flow-based Network for Text-to-Mel-spectrogram Synthesis.
    Model
    Tacotron2 and Waveglow 2.0 for PyTorch
    NVIDIA Deep Learning Examples
    The Tacotron 2 and WaveGlow model form a text-to-speech system that enables user to synthesise a natural sounding speech from raw transcripts.
    Resource
    FastPitch checkpoint (PyTorch, AMP, LJSpeech-1.1, 22050Hz)
    NVIDIA Deep Learning Examples
    FastPitch PyTorch checkpoint trained on LJSpeech-1.1
    Model

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