pruning

《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

[CVPR 2023] DepGraph: Towards Any Structural Pruning; LLMs, Vision Foundation Models, etc.

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

Practical course about Large Language Models.

Neural Network Compression Framework for enhanced OpenVINO™ inference

[EMNLP 2024 & AAAI 2026] A powerful toolkit for compressing large models including LLMs, VLMs, and video generative models.

reference pytorch code for named entity tagging

🛠️ Tools for Transformers compression using PyTorch Lightning ⚡

reference pytorch code for intent classification

Curated list of methods that focuses on improving the efficiency of diffusion models

Structured pruning, knowledge distillation, and fairness analysis for Large Language Models.

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models (ICLR 2022)