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Author:
AMD Research and Advanced Development
Summary:
Quantization-aware training in PyTorch
Latest version:
0.13.4
Required dependencies:
dependencies
|
packaging
|
setuptools
|
sympy
|
torch
|
typing-extensions
|
unfoldnd
Optional dependencies:
accelerate
|
bitstring
|
datasets
|
diffusers
|
filelock
|
gguf
|
hypothesis
|
inflect
|
ipython
|
jupyter
|
librosa
|
lighteval
|
lxml
|
m2r2
|
mock
|
nbmake
|
nbsphinx
|
nbsphinx-link
|
numba
|
numexpr
|
numpy
|
onnx
|
onnxoptimizer
|
onnxruntime
|
onnxscript
|
optimum
|
pandas
|
pillow
|
pre-commit
|
psutil
|
pydantic
|
pydata-sphinx-theme
|
pygments
|
pypandoc-binary
|
pytest
|
pytest-cases
|
pytest-mock
|
pytest-xdist
|
pyyaml
|
qonnx
|
requests
|
ruamel-yaml
|
scipy
|
soundfile
|
sox
|
sphinx
|
sphinx-autodoc-typehints
|
sphinx-gallery
|
sphinxcontrib-napoleon
|
sphinxemoji
|
toposort
|
torch
|
torch-stft
|
torchmetrics
|
torchvision
|
tqdm
|
transformers
|
unidecode
|
xxhash
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