Make sure to use Python 3.6+ and a virtual environment.
pip install nlp_architect
git clone https://github.com/IntelLabs/nlp-architect.git cd nlp-architect pip install -e . # install in development mode
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]
NLP Architect has the following packages:
|nlp_architect.api||Model API interfaces|
|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.utils||Misc. I/O, metric, pre-processing and text utilities|
NLP Architect comes with a CLI application that helps users run procedures and processes from the library.
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
nlp-train/inference -h for per command usage instructions.