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Train, evaluate, and run machine learning models.

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4,492 projects

torchdistill

yoshitomo-matsubara

1,636stars
torchdistill preview

A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆28 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

APDTFlow

yotambraun

44stars
APDTFlow preview

APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordinary differential equations (Neural ODEs), transformer-based components, and probabilistic modeling. Its modular design allows researchers and practitioners to experiment with multiple forecasting models and easily

Awesome-FL

youngfish42

2,018stars

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Machine LearningPythonCC-BY-SA-4.0GitHub
1,134stars
Anime-InPainting preview

An application tool of edge-connect, which can do anime inpainting and drawing. 动漫人物图片自动修复,去马赛克,填补,去瑕疵

mini-nanoGPT

ystemsrx

386stars
mini-nanoGPT preview

One-click training of your own GPT. Training a GPT has never been easier for beginners. / 一键预训练+SFT一个属于自己的LLM,0基础训练GPT原来可以这么简单?

  • 🔤 Flexible Tokenization — Character-level or custom tokenizers (Qwen, etc.)
  • 🚄 Efficient Training — Multi-process acceleration & distributed training

AAAMLP-CN

ytzfhqs

1,989stars

Approaching (Almost) Any Machine Learning Problem中译版,在线文档地址:https://ytzfhqs.github.io/AAAMLP-CN/

Machine LearningJupyter NotebookGitHub

TorchSeg

yu-changqian

1,409stars
TorchSeg preview

Fast, modular reference implementation and easy training of Semantic Segmentation algorithms in PyTorch.

  • Modular Design: easily construct customized semantic segmentation models by combining different components.
  • Distributed Training: >60% faster than the multi-thread parallel method(nn.DataParallel), we use the multi-processing parallel method.
1,091stars
noise2noise preview

An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"

971stars
ai-audio-datasets preview

AI Audio Datasets (AI-ADS) 🎵, including Speech, Music, and Sound Effects, which can provide training data for Generative AI, AIGC, AI model training, intelligent audio tool development, and audio applications.

ast

YuanGongND

1,485stars
ast preview

Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".

Machine LearningJupyter NotebookBSD-3-ClauseGitHub
778stars
Awesome-RGBT-Fusion preview

A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.

1,231stars
Entity-Relation-Extraction preview

Entity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取,2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019

1,172stars
Machine-Learning-Book preview

《机器学习宝典》包含:谷歌机器学习速成课程(招式)+机器学习术语表(口诀)+机器学习规则(心得)+机器学习中的常识性问题 (内功)。该资源适用于机器学习、深度学习研究人员和爱好者参考!

Machine LearningJupyter NotebookGitHub

rebiber

yuchenlin

3,045stars

A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).

AD-NeRF

YudongGuo

1,072stars
AD-NeRF preview

This repository contains a PyTorch implementation of "AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis".