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Escaping the Big Data Paradigm with Compact Transformers, 2021 (Train your Vision Transformers in 30 mins on CIFAR-10 with a single GPU!)
🤯 Lobe Chat - an open-source, modern-design AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Ollama / DeepSeek / Qwen), Knowledge Base (file upload / knowledge managemen…
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.
Intel staging area for llvm.org contribution. Home for Intel LLVM-based projects.
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
[CVPR 2024] Code release for "InstanceDiffusion: Instance-level Control for Image Generation"
HunyuanVideo-I2V: A Customizable Image-to-Video Model based on HunyuanVideo
High-Resolution 3D Assets Generation with Large Scale Hunyuan3D Diffusion Models.
HunyuanVideo: A Systematic Framework For Large Video Generation Model
JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️
Efficient baselines for autocurricula in JAX.
EvoRL is a fully GPU-accelerated framework for Evolutionary Reinforcement Learning, implemented with JAX. It supports Reinforcement Learning (RL), Evolutionary Computation (EC), Evolution-guided Re…
Official PyTorch implementation for "Large Language Diffusion Models"
Moshi is a speech-text foundation model and full-duplex spoken dialogue framework. It uses Mimi, a state-of-the-art streaming neural audio codec.
[NeurIPS 2024] A Generalizable World Model for Autonomous Driving
OpenGL Graphics Engine in Python ( Pygame, ModernGL )
Python Software 3D Engine (Object Renderer) with Pygame, Numpy, Numba
Self-contained, minimalistic implementation of diffusion models with Pytorch.
Reflexive & Persistent System (artificial intelligence)
A Python implementation of the Hopfield network