Metadata-Version: 2.3
Name: rau
Version: 0.2.0
Summary: Neural language modeling and sequence-to-sequence transduction in PyTorch.
License: MIT
Author: Brian DuSell
Author-email: brian.dusell@inf.ethz.ch
Requires-Python: >=3.11
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: humanfriendly (>=10.0,<11.0)
Requires-Dist: more-itertools (>=10.1.0,<11.0.0)
Requires-Dist: numpy (>=1.26.4,<2.0.0)
Requires-Dist: torch (>=2.1.0,<3.0.0)
Project-URL: Repository, https://github.com/bdusell/rau
Description-Content-Type: text/x-rst

Rau
===

Rau (rhymes with "now") is a Python module and command-line tool that provides
PyTorch implementations of neural network-based language modeling and
sequence-to-sequence generation. It is primarily suited for academic
researchers. Out of the box, it provides implementations of the simple
recurrent neural network (RNN), long short-term memory (LSTM), and transformer
architectures. It includes extensible Python APIs and command-line tools for
data preprocessing, training, and evaluation. It is very easy to get started
with the command-line tools if you provide your data in plaintext as lines of
space-separated tokens.

Read the full documentation `here <https://bdusell.github.io/rau/>`_.

