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🤯 LobeHub - an open-source, modern design AI Agent Workspace. Supports multiple AI providers, Knowledge Base (file upload / RAG ), one click install MCP Marketplace and Artifacts / Thinking. One-cl…
Minimal reproduction of DeepSeek R1-Zero
Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek, Qwen, Llama, Gemma, TTS 2x faster with 70% less VRAM.
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more.
This repository contains a Jupyter Notebook that implements Gaussian Mixture Model (GMM) for semantic segmentation and background extraction. GMM class is implemented from scratch without using any…
SCoRe: Training Language Models to Self-Correct via Reinforcement Learning
🚀🚀 「大模型」2小时完全从0训练26M的小参数GPT！🌏 Train a 26M-parameter GPT from scratch in just 2h!
Official Implementation for the paper "SR-AIF: Solving Sparse-Reward Robotic Tasks from Pixels with Active Inference and World Models"
A simple and efficient Mamba implementation in pure PyTorch and MLX.
[NeurIPS 2024] The official code of "U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers"
CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
Official code for "World Models via Policy-Guided Trajectory Diffusion", TMLR 2024
GLIDE: a diffusion-based text-conditional image synthesis model
Elucidating the Design Space of Diffusion-Based Generative Models (EDM)
This repository contains a collection of resources and papers on Diffusion Models for RL, accompanying the paper "Diffusion Models for Reinforcement Learning: A Survey"
A curated list of Diffusion Model in RL resources (continually updated)
Creating a diffusion model from scratch in PyTorch to learn exactly how they work.
Code for the paper "Planning with Diffusion for Flexible Behavior Synthesis"
A package for computing data-driven approximations to the Koopman operator.
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.