Aprendizaje automático · GitHub

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 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

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

[CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.

验证码识别

Conversión de modelos de aprendizaje profundo para distintos frameworks y programas de aprendizaje profundo.

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

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.

Keras implementation of a CNN network for age and gender estimation

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

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.

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

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.

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

《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！

中文nlp解决方案(大模型、数据、模型、训练、推理)

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

Stanford sky images and PV power generation dataset for solar forecasting related research and applications