.github Add CI for Arm Linux (#2211) May 16, 2025 benchmarks Feat: Implementation of the DeepSeek blockwise quantization for fp8 t… May 13, 2025 docs Micro-benchmark inference (#1759) Mar 18, 2025 examples Update ruff version to 0.11.6 (#2103) ...
Modules:https://github.com/pytorch/pytorch/tree/master/torch/nn/quantized/dynamic/modules Examples/tests:https://github.com/pytorch/pytorch/tree/master/test/test_nn_quantized.py Quantization QAT modules:https://github.com/pytorch/pytorch/tree/master/torch/nn/qat/modules Examples/tests: : https...
A pytorch quantization backend for optimum. Contribute to huggingface/optimum-quanto development by creating an account on GitHub.
Update quantization_aware_training.py Mar 27, 2022 train.py add folding bn relu Aug 26, 2020 Repository files navigation README Apache-2.0 license pytorch-quantization-demo A simple network quantization demo using pytorch from scratch. This is the code for mytutorialabout network quantization written...
git clone git@github.com:yhwang-hub/yolov7_quantization.git 2.Install dependencies pip install pytorch-quantization --extra-index-url https://pypi.ngc.nvidia.com 3.Prepare coco dataset .├── annotations │ ├── captions_train2017.json │ ├── captions_val2017.json │ ├── instan...
acceleratehttps://github.com/huggingface/accelerate from transformers import AutoModelForCausalLM, AutoTokenizer, QuantoConfigmodel_id = "facebook/opt-125m"tokenizer = AutoTokenizer.from_pretrained(model_id)quantization_config = QuantoConfig(weights="int8")quantized_model = AutoModelForCausalLM.from_...
Other hardware will transfer HardSwish and HardSigmoid to CPU automatically. Besides, we do support ReLU6. The warning you have got is for equalization to improve quantization accuracy. could you explain how to deploy HardSwish on CPU? is there any example? Thanks...
code:https://github.com/Forggtensky/Quantize_Pytorch_Vgg16AndMobileNet 第一部分,对pytorch的3种量化方式进行梳理,参考文献:https://pytorch.org/docs/stable/quantization.html 第二部分,我会附上采用后两张量化方式(Static and QAT)对VGG-16以及Mobilenet-V2网络的量化压缩。
Please see more detailed design doc at:https://github.com/pytorch/pytorch/wiki/torch_quantization_design_proposal. This document outlines a eager friendly quantization design. jgong5 reacted with thumbs up emoji 👍 Sorry, something went wrong. ...
Today, we are excited to introduce [🤗 quanto](https://github.com/huggingface/quanto), a versatile pytorch quantization toolkit, that provides several unique features: - available in eager mode (works with non-traceable models) - quantized models can be placed on any device (including CUDA an...