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NeMo: a toolkit for conversational AI

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NVIDIA NeMo

Introduction

NeMo is a toolkit for creating Conversational AI <https://developer.nvidia.com/conversational-ai#started>_ applications.

NeMo product page. <https://developer.nvidia.com/nvidia-nemo>_

Introductory video. <https://www.youtube.com/embed/wBgpMf_KQVw>_

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

  • Automatic Speech Recognition (ASR) <https://ngc.nvidia.com/catalog/models/nvidia:nemospeechmodels>_
  • Natural Language Processing (NLP) <https://ngc.nvidia.com/catalog/models/nvidia:nemonlpmodels>_
  • Speech synthesis, or Text-To-Speech (TTS) <https://ngc.nvidia.com/catalog/models/nvidia:nemottsmodels>_

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.

.. code-block:: bash

    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).

.. code-block:: bash

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.

.. code-block:: bash

    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 <https://ngc.nvidia.com/catalog/containers/nvidia:nemo>_.
It has all requirements and NeMo 1.0.0b3 already installed.

.. code-block:: bash

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.

.. code-block:: bash

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. <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/NeMo_voice_swap_app.ipynb>_ (runs in Google Colab, no local installation necessary)

Lots of other examples in "Examples" folder. <https://github.com/NVIDIA/NeMo/tree/main/examples>_

Documentation

.. |main| image:: https://readthedocs.com/projects/nvidia-nemo/badge/?version=main
:alt: Documentation Status
:scale: 100%
:target: https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/

.. |v1.0.0b1| image:: https://readthedocs.com/projects/nvidia-nemo/badge/?version=v1.0.0b1
:alt: Documentation Status
:scale: 100%
:target: https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/v1.0.0b1/

+---------+------------+----------------------------------------------------------------------------------------------------------------------------------+
| Version | Status | Description |
+=========+============+==================================================================================================================================+
| Latest | |main| | Documentation of the latest (i.e. main) branch <https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/>_ |
+---------+------------+----------------------------------------------------------------------------------------------------------------------------------+
| Stable | |v1.0.0b1| | Documentation of the stable (i.e. v1.0.0b1) branch <https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/v1.0.0b1/>_ |
+---------+------------+----------------------------------------------------------------------------------------------------------------------------------+

Getting help with NeMo

FAQ can be found on NeMo's Discussions board <https://github.com/NVIDIA/NeMo/discussions>_. 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 <https://colab.research.google.com/notebooks/intro.ipynb>_.

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)

.. list-table:: Tutorials
:widths: 15 25 25
:header-rows: 1

    • Domain
    • Title
    • GitHub URL
    • NeMo
    • Simple Application with NeMo
    • Voice swap app <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/NeMo_voice_swap_app.ipynb>_
    • NeMo
    • Exploring NeMo Fundamentals
    • NeMo primer <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/00_NeMo_Primer.ipynb>_
    • NeMo Models
    • Exploring NeMo Model Construction
    • NeMo models <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/01_NeMo_Models.ipynb>_
    • ASR
    • ASR with NeMo
    • ASR with NeMo <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/asr/01_ASR_with_NeMo.ipynb>_
    • ASR
    • ASR with Subword Tokenization
    • ASR with Subword Tokenization <https://colab.research.google.com/github/NVIDIA/NeMo/blob/main/tutorials/asr/08_ASR_with_Subword_Tokenization.ipynb>_
    • ASR
    • Speech Commands
    • Speech commands <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/asr/03_Speech_Commands.ipynb>_
    • ASR
    • Speaker Recognition and Verification
    • Speaker Recognition and Verification <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/speaker_recognition/Speaker_Recognition_Verification.ipynb>_
    • ASR
    • Online Noise Augmentation
    • Online noise augmentation <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/asr/05_Online_Noise_Augmentation.ipynb>_
    • ASR
    • Beam Search and External Language Model Rescoring
    • Beam search and external language model rescoring <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/asr/Offline_ASR.ipynb>_
    • NLP
    • Using Pretrained Language Models for Downstream Tasks
    • Pretrained language models for downstream tasks <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/01_Pretrained_Language_Models_for_Downstream_Tasks.ipynb>_
    • NLP
    • Exploring NeMo NLP Tokenizers
    • NLP tokenizers <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/02_NLP_Tokenizers.ipynb>_
    • NLP
    • Text Classification (Sentiment Analysis) with BERT
    • Text Classification (Sentiment Analysis) <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Text_Classification_Sentiment_Analysis.ipynb>_
    • NLP
    • Question answering with SQuAD
    • Question answering Squad <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Question_Answering_Squad.ipynb>_
    • NLP
    • Token Classification (Named Entity Recognition)
    • Token classification: named entity recognition <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Token_Classification_Named_Entity_Recognition.ipynb>_
    • NLP
    • Joint Intent Classification and Slot Filling
    • Joint Intent and Slot Classification <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Joint_Intent_and_Slot_Classification.ipynb>_
    • NLP
    • GLUE Benchmark
    • GLUE benchmark <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/GLUE_Benchmark.ipynb>_
    • NLP
    • Punctuation and Capitialization
    • Punctuation and capitalization <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Punctuation_and_Capitalization.ipynb>_
    • NLP
    • Named Entity Recognition - BioMegatron
    • Named Entity Recognition - BioMegatron <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Token_Classification-BioMegatron.ipynb>_
    • NLP
    • Relation Extraction - BioMegatron
    • Relation Extraction - BioMegatron <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Relation_Extraction-BioMegatron.ipynb>_
    • TTS
    • Speech Synthesis
    • TTS inference <https://colab.research.google.com/github/NVIDIA/NeMo/blob/v1.0.0b4/tutorials/tts/1_TTS_inference.ipynb>_
    • TTS
    • Speech Synthesis
    • Tacotron2 training <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0b4/tutorials/tts/2_TTS_Tacotron2_Training.ipynb>_
    • Tools
    • CTC Segmentation
    • CTC Segmentation <https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/tools/CTC_Segmentation_Tutorial.ipynb>_
    • Tools
    • Text Normalization for Text To Speech
    • Text Normalization <https://colab.research.google.com/github/NVIDIA/NeMo/blob/main/tutorials/tools/Text_Normalization_Tutorial.ipynb>_

Contributing

We welcome community contributions! Please refer to the CONTRIBUTING.md <https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md>_ CONTRIBUTING.md for the process.

License

NeMo is under Apache 2.0 license <https://github.com/NVIDIA/NeMo/blob/main/LICENSE>_.

Languages

Jupyter Notebook90.7%Python9.3%Shell0.0%Dockerfile0.0%
Apache License 2.0
Created March 10, 2021
Updated August 29, 2025