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Author: AMD Research and Advanced Development
Summary: Quantization-aware training in PyTorch
Latest version: 0.12.1
Required dependencies: dependencies | numpy | packaging | setuptools | sympy | torch | typing-extensions | unfoldnd
Optional dependencies: accelerate | bitstring | datasets | diffusers | gguf | hypothesis | inflect | jupyter | librosa | lm-eval | lxml | m2r2 | mock | nbmake | nbsphinx | nbsphinx-link | numba | numpy | onnx | onnxoptimizer | onnxruntime | onnxscript | optimum | pandas | pillow | pre-commit | psutil | pydata-sphinx-theme | 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

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