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.
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.server | API Server and demos UI |
nlp_architect.solutions | Solution applications |
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
The list of possible options can be obtained by nlp_architect -h
:
nlp_architect
commands:
train Train a model from the library
run Run a model from the library
process Run a data processor from the library
solution Run a solution process from the library
serve Server a trained model using REST service
Use nlp_architect <command> -h
for per command usage instructions.