EmoSense

《李宏毅深度学习教程》（李宏毅老师推荐?，苹果书?），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Sparsity-aware deep learning inference runtime for CPUs

Flops counter for convolutional networks in pytorch framework

A curated list of neural network pruning resources.

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

[NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang

PaddleSlim is an open-source library for deep model compression and architecture search.

OpenMMLab Model Compression Toolbox and Benchmark.

Practical course about Large Language Models.

A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.