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I implemented a transformer model from scratch using PyTorch, based on the paper Attention is All You Need. You can use my scripts to train your own billion or million parameter LLM using a single GPU.

Reef is the first open-source infrastructure for continual self-improving agents. It connects agent inference, feedback, learning, and versioned delivery. Use it to train model weights with Slime and SGLang, or improve an agent's harness, including its prompts, rules, and skills.

Easily train a good VC model with voice data <= 10 mins!

AI Toolkit is an easy to use all in one training suite for diffusion models. I try to support all the latest models on consumer grade hardware. Image and video models.

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

The scripts load VPP2 directly from this checkout; installing the vpp2 package is unnecessary. txt.

GPU-optimized library for training transformer models at scale

Welcome to the magical world of Diffusion models! DiffSynth-Studio is an open-source Diffusion model engine developed and maintained by the ModelScope Community team.

This release contains training, two inference backends, benchmark scoring, temperature calibration, and a browser demo.

A training framework that elicits proactive reflection in tool-using LLM agents: noticing noisy tool feedback and user corrections, and recovering from them.

This is the official repository for Attention Residuals (AttnRes), a drop-in replacement for standard residual connections in Transformers that enables each layer to selectively aggregate earlier representations via learned, input-dependent attention over depth.

Gaussian blur reveals how Valen-Preview-0923 adapts its decisions and confidence as visual detail decreases. 2% at the strongest blur.

pytorch/examples is a repository showcasing examples of using PyTorch. The goal is to have curated, short, few/no dependencies high quality examples that are substantially different from each other that can be emulated in your existing work.

The following is the corresponding torchvision versions and supported Python versions.

Ultralytics YOLOv5 🚀 is a fast, accurate, and easy-to-use computer vision model developed by Ultralytics. Based on the PyTorch framework, YOLOv5 is renowned for its speed, accuracy, and simplicity.

Training neural networks on Apple Neural Engine via reverse-engineered private APIs

DeepSpec is a full-stack codebase for training and evaluating draft models for speculative decoding. It contains data preparation utilities, draft model implementations, training code, and evaluation scripts.

mini-AGI - is a continual learning byte-level language model that assembles its own architecture, trains from scratch on a single 8 GB VRAM GPU, and keeps learning from everything it reads.

5 FM → Stage1 TF-AnyFlow → Stage2 DMD via SGF, turning a bidirectional video model into a camera-controlled few-step autoregressive model.

A fully open reproduction of DeepSeek-R1. This repo is a work in progress, let's build it together!

This repository contains Stability AI's ongoing development of the StableLM series of language models and will be continuously updated with new checkpoints. The following provides an overview of all currently available models. More coming soon.

LittleBit compresses large language models into the sub-1-bit regime by factorizing each dense weight matrix into low-rank latent factors, binarizing those factors, and restoring magnitude information through lightweight learned scales.

0 NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

Ultralytics YOLOv3 is a PyTorch implementation of the YOLOv3 (You Only Look Once, version 3) real-time object detection model.

Meshy models every role of an RL run as an independent service. Samples flow between services through a single TransferQueue data plane, control flow is driven by data availability, and the whole topology is derived locally by each process from one declarative recipe.

Solution of Team sdkxd for MICCAI 2023 Challenges: STS - Tooth Segmentation Task Based on 3D CBCT

PointDiT is a minimalist pixel-space Diffusion Transformer for monocular geometry estimation.

5 series unified generative models. It is designed to be easily adapted for your own tasks — you only need to swap in your own data loader and RL reward function.