Fake Sora API is an open-source project that simulates the yet-to-be-released OpenAI Sora API, enabling developers to prepare and test their applications in advance.

Generative Agents: Interactive Simulacra of Human Behavior

Fast ChatGPT UI with support for both OpenAI and Azure OpenAI. 快速的ChatGPT UI，支持OpenAI和Azure OpenAI。

🦜🔗 Build context-aware reasoning applications

ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型

Making large AI models cheaper, faster and more accessible

Minimal web UI for ChatGPT.

(CVPR 2023) Pytorch implementation of “T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations”

The official PyTorch implementation of the paper "Human Motion Diffusion Model"

Modern Shadowsocks in Go

ICLR 2021: Noise against noise: stochastic label noise helps combat inherent label noise

OpenMMLab Pose Estimation Toolbox and Benchmark.

An implementation of the TrueSkill rating system for Python

A unified framework of perturbation and gradient-based attribution methods for Deep Neural Networks interpretability. DeepExplain also includes support for Shapley Values sampling. (ICLR 2018)

The release codes of LA-MCTS with its application to Neural Architecture Search.

AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise

AAAI 2021: Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Multi-Hop Logical Reasoning in Knowledge Graphs

Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.

A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

Code for visualizing the loss landscape of neural nets

A curated list of resources for Learning with Noisy Labels

Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning

GPU Accelerated t-SNE for CUDA with Python bindings

Best CIFAR-10, CIFAR-100 results with wide-residual networks using PyTorch