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.. |status| image:: http://www.repostatus.org/badges/latest/active.svg
:target: http://www.repostatus.org/#active
:alt: Project Status: Active – The project has reached a stable, usable state and is being actively developed.
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:target: https://github.com/NVIDIA/NeMo/blob/master/LICENSE
:alt: NeMo core license and license for collections in this repo
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:target: https://lgtm.com/projects/g/NVIDIA/NeMo/context:python
:alt: Language grade: Python
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**NVIDIA NeMo**
===============
Train State of the Art AI Models
--------------------------------
**Introduction**
NeMo is a toolkit for creating `Conversational AI <https://developer.nvidia.com/conversational-ai#started>`_ applications.
NeMo toolkit makes it possible for researchers to easily compose complex neural network architectures for conversational AI using reusable components - Neural Modules.
**Neural Modules** are conceptual blocks of neural networks that take *typed* inputs and produce *typed* outputs. Such modules typically represent data layers, encoders, decoders, language models, loss functions, or methods of combining activations.
The toolkit comes with extendable collections of pre-built modules and ready-to-use models for automatic speech recognition (ASR), natural language processing (NLP) and text synthesis (TTS).
Built for speed, NeMo can utilize NVIDIA's Tensor Cores and scale out training to multiple GPUs and multiple nodes.
`Documentation <https://docs.nvidia.com/deeplearning/nemo/developer_guide/en/candidate/>`_
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Requirements
------------
NeMo's works with:
1) Python 3.6 or 3.7
2) Pytorch 1.6 or above
Installation
~~~~~~~~~~~~
``pip install nemo_toolkit[all]==version``
We recommend using NVIDIA's PyTorch container
.. 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 nvcr.io/nvidia/pytorch:20.06-py3
