PyPI page
Author:
Rudy van den Brink
Summary:
A package for automated hyper parameter tuning and machine learning workflows. Build an end-to-end pipeline or fine tune an LLM on consumer hardware in a few lines of code.
Latest version:
1.1.3
Required dependencies:
asttokens
|
bs4
|
colorama
|
comm
|
contractions
|
datasets
|
debugpy
|
decorator
|
executing
|
imbalanced-learn
|
ipykernel
|
ipython
|
ipython-pygments-lexers
|
jedi
|
joblib
|
jupyter-client
|
jupyter-core
|
matplotlib
|
matplotlib-inline
|
nest-asyncio
|
numpy
|
packaging
|
pandas
|
parso
|
peft
|
platformdirs
|
prompt-toolkit
|
psutil
|
pure-eval
|
pygments
|
python-dateutil
|
pytz
|
pywin32
|
pyzmq
|
scikit-learn
|
scikit-optimize
|
scipy
|
seaborn
|
six
|
stack-data
|
stanza
|
tabulate
|
textblob
|
threadpoolctl
|
torch
|
torchaudio
|
torchvision
|
tornado
|
tqdm
|
traitlets
|
typing-extensions
|
tzdata
|
wcwidth
|
xgboost
Optional dependencies:
build
|
setuptools
|
twine
|
wheel
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