Train speculative decoding models effortlessly and port them smoothly to SGLang serving.

Best practices & guides on how to write distributed pytorch training code

Fault tolerance for PyTorch (HSDP, LocalSGD, DiLoCo, Streaming DiLoCo)

Repo for Qwen Image Finetune

META LLAMA3 GENAI Real World UseCases End To End Implementation Guide

Llama-style transformer in PyTorch with multi-node / multi-GPU training. Includes pretraining, fine-tuning, DPO, LoRA, and knowledge distillation. Scripts for dataset mixing and training from scratch.

🦾💻🌐 distributed training & serverless inference at scale on RunPod

A comprehensive hands-on guide to building production-grade distributed applications with Ray - from distributed training and multimodal data processing to inference and reinforcement learning.

Fast and easy distributed model training examples.

A script for training the ConvNextV2 on CIFAR10 dataset using the FSDP technique for a distributed training scheme.

Simple and efficient implementation of 671B DeepSeek V3 that trainable with FSDP+EP and minimal requirement of 256x A100/H100, targeted for HuggingFace ecosystem

Minimal yet high performant code for pretraining llms. Attempts to implement some SOTA features. Implements training through: Deepspeed, Megatron-LM, and FSDP. WIP

A minimal, hackable pre-training stack for GPT-style language models

Framework, Model & Kernel Optimizations for Distributed Deep Learning - Data Hack Summit

Implementations of some popular approaches for efficient deep learning training and inference

Dataloading for JAX

Scalable multimodal AI system combining FSDP, RLHF, and Inferentia optimization for customer insights generation.

🎨 Generate high-quality images with the Qwen-Image model, a powerful text-to-image tool optimized for fast and efficient deployment on serverless architecture.

A foundational repository for setting up distributed training jobs using Kubeflow and PyTorch FSDP.

Mini-FSDP for PyTorch. Minimal single-node Fully Sharded Data Parallel wrapper with param flattening, grad reduce-scatter, AMP, and tiny GPT/BERT training examples.