Metadata-Version: 2.4
Name: textslinger
Version: 0.1.0
Summary: TextSlinger text prediction toolkit.
Author-email: Dylan Gaines <dcgaines@mtu.edu>, Keith Vertanen <vertanen@mtu.edu>, CAMBI <cambi_support@googlegroups.com>
License: MIT License
        
        Copyright (c) 2025 Keith Vertanen, Dylan Gaines
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, https://www.cambi.tech/
Project-URL: Source, https://github.com/kdv123/textpredict
Platform: Linux
Platform: Windows
Platform: Mac OS-X
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: Natural Language :: English
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: <3.11,>=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.md
Requires-Dist: torch==2.2.0
Requires-Dist: torchvision==0.17.0
Requires-Dist: torchaudio==2.2.0
Requires-Dist: datasets==2.0.0
Requires-Dist: bitsandbytes==0.42.0
Requires-Dist: requests==2.32.3
Requires-Dist: kenlm==0.1
Requires-Dist: nlpaug==1.1.11
Requires-Dist: psutil==5.7.2
Requires-Dist: ipywidgets==8.1.3
Requires-Dist: sentencepiece==0.2.0
Requires-Dist: protobuf==4.25.3
Requires-Dist: evaluate==0.4.0
Requires-Dist: scikit-learn==1.2.2
Requires-Dist: accelerate==0.33.0
Requires-Dist: transformers==4.47.0
Requires-Dist: numpy==1.24.4
Requires-Dist: tqdm==4.62.2
Provides-Extra: release
Requires-Dist: twine==5.0.0; extra == "release"
Requires-Dist: build==1.2.2.post1; extra == "release"
Requires-Dist: wheel==0.43.0; extra == "release"
Dynamic: license-file

Python library for making text predictions using a language model.

**** Setting up a Python environment ****
These instructions are the same as those in the classify-aac which actually does training of models.
But the same environment should also work for evaluation using the models (though you may only need a subset of the packages).
This was tested on cheetah on 9/14/24.

If you don't have anaconda installed in your user account you'll first need to do that.
See: https://docs.anaconda.com/anaconda/install/linux/

% conda create -n aacllm python=3.10
% conda activate aacllm
% conda install pytorch torchvision torchaudio pytorch-cuda cuda mpi4py -c pytorch -c nvidia
% pip install 'git+https://github.com/potamides/uniformers.git#egg=uniformers'
% pip install --upgrade transformers
% pip install kenlm==0.1 --global-option="--max_order=12"
% pip install rbloom bitsandbytes requests nlpaug ipywidgets psutil datasets sentencepiece protobuf evaluate scikit-learn deepspeed accelerate
