Awesome Knowledge Distillation

Awesome Knowledge-Distillation. 分ぶん类整理せいり的てき知ち识蒸馏paper(2014-2021)。

Pytorch implementation of various Knowledge Distillation (KD) methods.

This repository collects papers for "A Survey on Knowledge Distillation of Large Language Models". We break down KD into Knowledge Elicitation and Distillation Algorithms, and explore the Skill & Vertical Distillation of LLMs.

SimpleAICV:pytorch training and testing examples.

模型もけい压缩的てき小しょう白しろ入にゅう门教程ほど

Official implementation of paper "Knowledge Distillation from A Stronger Teacher", NeurIPS 2022

[ECCV2022] Factorizing Knowledge in Neural Networks

Training ImageNet / CIFAR models with sota strategies and fancy techniques such as ViT, KD, Rep, etc.

Awesome-3D/Multimodal-Anomaly-Detection-and-Localization/Segmentation/3D-KD/3D-knowledge-distillation

Official implementation of paper "Masked Distillation with Receptive Tokens", ICLR 2023.

Matching Guided Distillation (ECCV 2020)

Rotated Localization Distillation (CVPR 2022, TPAMI 2023)

Engine for communication with remote kernel debugger (KD, WinDbg) from drivers and applications

Cross-platform Python scripts to interface with the Microsoft Kernel Debugger

A unified cGAN-based knowledge distillation method

A simple script to convert Agilent 845x Chemstation UV-Vis files (.KD or .SD formats) to .csv format. Fast and easy!

Documentation for Ki Libraries and Languages

Pluto notebook for curve fitting

This is a Kotlin implementation of the KD language. It is feature complete and passes all tests.