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NeMo: a toolkit for conversational AI

Home Page: https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/

License: Apache License 2.0

Python 35.12% Shell 0.10% Dockerfile 0.05% Jupyter Notebook 64.73%

nemo's Introduction

Project Status: Active โ€“ The project has reached a stable, usable state and is being actively developed. Documentation NeMo core license and license for collections in this repo Language grade: Python Total alerts Code style: black

NVIDIA NeMo

Introduction

NeMo is a toolkit for creating Conversational AI applications.

NeMo product page.

Introductory video.

The toolkit comes with extendable collections of pre-built modules and ready-to-use models for:

Built for speed, NeMo can utilize NVIDIA's Tensor Cores and scale out training to multiple GPUs and multiple nodes.

Requirements

  1. Python 3.6 or above
  2. Pytorch 1.7.1 or above

Installation

Pip

Use this installation mode if you want the latest released version.

apt-get update && apt-get install -y libsndfile1 ffmpeg
pip install Cython
pip install nemo_toolkit[all]==1.0.0b3

Pip from source

Use this installation mode if you want the a version from particular GitHub branch (e.g main).

apt-get update && apt-get install -y libsndfile1 ffmpeg
pip install Cython
python -m pip install git+https://github.com/NVIDIA/NeMo.git@{BRANCH}#egg=nemo_toolkit[all]

From source

Use this installation mode if you are contributing to NeMo.

apt-get update && apt-get install -y libsndfile1 ffmpeg
git clone https://github.com/NVIDIA/NeMo
cd NeMo
./reinstall.sh

Docker containers:

The easiest way to start training with NeMo is by using NeMo's container. It has all requirements and NeMo 1.0.0b3 already installed.

docker run --gpus all -it --rm --shm-size=8g \
-p 8888:8888 -p 6006:6006 --ulimit memlock=-1 --ulimit \
stack=67108864 --device=/dev/snd nvcr.io/nvidia/nemo:1.0.0b3

If you chose to work with main branch, we recommend using NVIDIA's PyTorch container version 20.11-py3 and then installing from GitHub.

docker run --gpus all -it --rm -v <nemo_github_folder>:/NeMo --shm-size=8g \
-p 8888:8888 -p 6006:6006 --ulimit memlock=-1 --ulimit \
stack=67108864 --device=/dev/snd nvcr.io/nvidia/pytorch:20.11-py3

Examples

Simplest application with NeMo. (runs in Google Colab, no local installation necessary)

Lots of other examples in "Examples" folder.

Documentation

Version Status Description
Latest Documentation Status Documentation of the latest (i.e. main) branch
Stable Documentation Status Documentation of the stable (i.e. v1.0.0b1) branch

Getting help with NeMo

FAQ can be found on NeMo's Discussions board. You are welcome to ask questions or start discussions there.

Tutorials

The best way to get started with NeMo is to checkout one of our tutorials.

Most NeMo tutorials can be run on Google's Colab.

To run tutorials:

  • Click on Colab link (see table below)
  • Connect to an instance with a GPU (Runtime -> Change runtime type -> select "GPU" for hardware accelerator)
Tutorials
Domain Title GitHub URL
NeMo Simple Application with NeMo Voice swap app
NeMo Exploring NeMo Fundamentals NeMo primer
NeMo Models Exploring NeMo Model Construction NeMo models
ASR ASR with NeMo ASR with NeMo
ASR ASR with Subword Tokenization ASR with Subword Tokenization
ASR Speech Commands Speech commands
ASR Speaker Recognition and Verification Speaker Recognition and Verification
ASR Online Noise Augmentation Online noise augmentation
ASR Beam Search and External Language Model Rescoring Beam search and external language model rescoring
NLP Using Pretrained Language Models for Downstream Tasks Pretrained language models for downstream tasks
NLP Exploring NeMo NLP Tokenizers NLP tokenizers
NLP Text Classification (Sentiment Analysis) with BERT Text Classification (Sentiment Analysis)
NLP Question answering with SQuAD Question answering Squad
NLP Token Classification (Named Entity Recognition) Token classification: named entity recognition
NLP Joint Intent Classification and Slot Filling Joint Intent and Slot Classification
NLP GLUE Benchmark GLUE benchmark
NLP Punctuation and Capitialization Punctuation and capitalization
NLP Named Entity Recognition - BioMegatron Named Entity Recognition - BioMegatron
NLP Relation Extraction - BioMegatron Relation Extraction - BioMegatron
TTS Speech Synthesis TTS inference
TTS Speech Synthesis Tacotron2 training
Tools CTC Segmentation CTC Segmentation
Tools Text Normalization for Text To Speech Text Normalization

Contributing

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

License

NeMo is under Apache 2.0 license.

nemo's People

Contributors

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Watchers

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