NVIDIA
NVIDIA
Nemo with Pytorch Lightning
Resource
NVIDIA
NVIDIA
Nemo with Pytorch Lightning

The primary objective of NeMo is to help researchers from industry and academia to reuse prior work and make it easier to create new conversational AI models.

Nemo with PyTorch Lightning

PyTorch Lightning is a light weight PyTorch wrapper that reduces the engineering boilerplate and resources required to implement state-of-the-art AI. Organizing PyTorch code with Lightning, enables seamless training on multiple-GPUs, TPUs, CPUs as well as the use of difficult to implement best practices such as model sharding, 16-bit precision and more. PyTorch Lightning support an extremly robust ecosystem of Machine Learning and Deep Learning projects from 1st Party Repos such as Flash to 3rd party frameworks such as Nvidia NeMo. NVIDIA NeMo is a conversational AI toolkit built for researchers working on automatic speech recognition (ASR), natural language processing (NLP), and text-to-speech synthesis (TTS). The primary objective of NeMo is to help researchers from industry and academia to reuse prior work (code and pretrained models and make it easier to create new conversational AI models.

Run the Jupyter notebook:

Download the jupyter notebook from top right section of this page and run the cells of the notebook to install required libraries, download the models and train the model.

Publisher
NVIDIA
NVIDIA
Latest Version1
UpdatedApril 4, 2023 UTC
Compressed Size1.78 MB

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking "Accept All", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on "Manage Settings." By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.