论文:Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT 最直接的方法,其实各个框架也都提供了相关函数,比如说TensorFlow Lite里就有自己的量化方案,而最近放出的 Pytorch 1.3 中也有关于量化的更新。 Tensorflow:https://www.tensorflow.org/
KD-Lib: A PyTorch library for Knowledge Distillation, Pruning and Quantization.Het ShahAvishree KhareNeelay ShahKhizir Siddiqui
Compress networks using PyTorch - Pruning and Quantization This is a complete training example for Deep Convolutional Networks on ImageNet. Currently, the compression methods based on several techniques below: Taylor Expansion (A good summary of this approach can be found here). Attention Transfer fro...
Train neural networks with joint quantization and pruning on both weights and activations using any pytorch modules - mlzxy/qsparse
All the experiments were conducted using pyTorch on M40 GPUs. Consistency of index code In this part, we want to discuss an interesting question about the consistency of index code. Since the generated binary code is used for model pruning, it should be unique for different input mini-batches...
Section 6 gives conclusions and an outlook to future work. 2. Related work We start the discussion of related research in the field of network compression with network quantization methods which have been proposed for storage space compression by decreasing the number of possible and unique values ...
Hawq: Hessian aware quantization of neural networks with mixed-precision. In Proceedings of the IEEE International Conference on Computer Vision, pages 293–302, 2019. 7 [12] Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unter...
pytorch模型剪枝 在cifar数据集上做图像分类的训练,并以此演示怎样进行模型剪枝,pytorch版本必须大于1.4.0 上传者:longma666666时间:2020-07-17 量化加速-使用Pytorch-quantization对YOLOv8目标检测算法进行量化加速-模型小型化-附项目源码优质项目实战 量化加速_使用Pytorch_quantization对YOLOv8目标检测算法进行量化加速_模型...
The Good, the Bad, and the Ugly: Cost-Efficient LLM Inference With Quantization, Pruning, and Distillation GTC session:Make My PyTorch Model Fast, and Show Me How You Did It GTC session:Keep Your GPUs Going Brrr : Crushing Whitespace in Model Training ...
(2015). Deep compression: compressing deep neural networks with pruning, trained quantization and huffman coding. arXiv preprint arXiv:1510.00149. He K et al. (2016). Deep residual learning for image recognition. In proceedings of the IEEE conference on computer vision and pattern recognition 770...