# Quick start

## Installation

Make sure to use Python 3.6+ and a virtual environment.

### Using `pip`

    pip install nlp_architect

### From source

    git clone https://github.com/NervanaSystems/nlp-architect.git
    cd nlp-architect
    pip install -e .  # install in development mode

Note

For specific installation of backends of Tensorflow or PyTorch (CPU/MKL/GPU) we recommend installing NLP Architect and then installing the desired package of framework.

## Running Examples and Solutions

To run provided examples and solutions please install the library with [all] flag which will install extra packages required. (requires installation from source)

    pip install .[all]

## Usage

NLP Architect has the following packages:

Package | Description
--- | ---
nlp_architect.api | Model API interfaces
nlp_architect.common | Common packages
nlp_architect.cli | Command line module
nlp_architect.data | Datasets, loaders and data processors
nlp_architect.models | NLP, NLU and End-to-End models
nlp_architect.nn | Topology related models and additions (per framework)
nlp_architect.pipelines | End-to-end NLP apps
nlp_architect.procedures | Procedure scripts
nlp_architect.utils | Misc. I/O, metric, pre-processing and text utilities

## CLI

NLP Architect comes with a CLI application that helps users run procedures and processes from the library.

Warning

The CLI is in development and some functionality is not complete and will be added in future versions

NLP Architect commands:

    nlp-train       Train a model from the library
    nlp-inference   Run a model from the library

Use `nlp-train/inference -h` for per command usage instructions.