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NVIDIA-NeMo logoNeMo

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

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README

Project Status: Active -- The project has reached a stable, usable state and is being actively developed. Documentation CodeQL NeMo core license and license for collections in this repo Release version Python version PyPi total downloads Code style: black

NVIDIA NeMo Speech

Checkout our HuggingFace🤗 collection for the latest open weight checkpoints and demos!

Updates

  • 2026-03: Nemotron-Speech-Streaming v2603 has been updated. It has been trained on a larger and more diverse corpus, resulting in lower WER across all latency modes. Try out the demo and check out the NIM.
  • 2026-03: MagpieTTS v2602 has been released with support for 9 languages(En, Es, De, Fr, Vi, It, Zh, Hi, Ja). Try out the demo and check out the NIM.
  • 2026-01: Nemotron-Speech-Streaming was released: One checkpoint that enables users to pick their optimal point on the latency-accuracy Pareto curve!
  • 2026-01: MagpieTTS was released.
  • 2026: This repo has pivoted to focus on audio, speech, and multimodal LLM. For the last NeMo release with support for more modalities, see v2.7.0
  • 2025-08: Parakeet V3 and Canary V2 have been released with speech recognition and translation support for 25 European languages.
  • 2025-06: Canary-Qwen-2.5B has been released with record-setting 5.63% WER on English Open ASR Leaderboard.

Introduction

NVIDIA NeMo Speech is built for researchers and PyTorch developers working on Speech models including Automatic Speech Recognition (ASR), Text to Speech (TTS), and Speech LLMs. It is designed to help you efficiently create, customize, and deploy new It is designed to help you efficiently create, customize, and deploy new AI models by leveraging existing code and pre-trained model checkpoints.

For technical documentation, please see the NeMo Framework User Guide.

Requirements

  • Python 3.12 or above
  • Pytorch 2.6 or above
  • NVIDIA GPU (if you intend to do model training)

As of Pytorch 2.6, torch.load defaults to using weights_only=True. Some model checkpoints may require using weights_only=False. In this case, you can set the env var TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD=1 before running code that uses torch.load. However, this should only be done with trusted files. Loading files from untrusted sources with more than weights only can have the risk of arbitrary code execution.

Developer Documentation

VersionStatusDescription
LatestDocumentation StatusDocumentation of the latest (i.e. main) branch.
StableDocumentation StatusDocumentation of the stable (i.e. most recent release) - To be added

Install NeMo Speech

NeMo Speech is installable via pip: pip install 'nemo-toolkit[all]' To install with extra dependencies for CUDA 12.x or 13.x, use pip install 'nemo-toolkit[all,cu12]' or pip install 'nemo-toolkit[all,cu13]' respectively.

Contribute to NeMo

We welcome community contributions! Please refer to CONTRIBUTING.md for the process.

Licenses

NeMo is licensed under the Apache License 2.0.