Popular GitHub Repositories for Kd

Awesome Knowledge Distillation

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

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.

?《统计学习方法-李航: 笔记》 200页PDF，公式细节讲解?

模型压缩的小白入门教程

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品

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

由时间空间成对组成的轨迹序列，通过循环神经网络lstm，自编码器auto-encode，时空密度聚类st-dbscan做异常检测

Fine-tuned BERT on SQuAd 2.0 Dataset. Applied Knowledge Distillation (KD) and fine-tuned DistilBERT (student) using BERT as the teacher model. Reduced the size of the original BERT by 40%.

KD Gemini-Pro, a desktop application on PyQt5, simplifies interaction with Google's Gemini-Pro AI model. Users effortlessly submit questions, receiving instant, generated responses. With an intuitive interface and advanced features, it efficiently explores the capabilities of AI-assisted conversation.

Streamlit-based dashboard that collect, aggr. and visualize player's stats from Call of Duty Warzone1. Also deploy our model (cf. /match2kd repo) to predict game difficulty ("lobby kd") from game features.

Save thousands of API calls. Custom model & dataset aiming at predicting a game difficulty score ("lobby avg kd") without calling players' games history stats and profiles.

Projects Implemented for the Udacity Sensor Fusion Engineer Nanodegree Program

a FAQ knowledge base supported QA-system，it applies multiple text-matching algorithm，including：1.sequence classification model(Bert+TextRCNN，Bert+Qwen2)。2.BM25。3.KD-Tree

Fast semantic OS Search

Facial Landmark Detection Using Knowledge Distillation-Based Neural Networks

Example implementation of VectorMap-Index for laptop recommendation using KD-Tree + local hash + Ollama embeddings.

Efficient NLVL on Ego4D. Benchmark VSLBase/VSLNet with BERT/GloVE, EgoVLP/Omnivore, configurable FiLM conditioning layer (Perez et al., FiLM: Visual Reasoning with a General Conditioning Layer), explores compression via KD, including CBKD (Lan et al., Counterclockwise Block‑by‑Block Knowledge Distillation), prototype post‑training quantization.