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

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

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

META LLAMA3 GENAI Real World UseCases End To End Implementation Guide

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

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

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.

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

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

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

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

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

Dataloading for JAX

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

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.

Training Qwen3 to solve Wordle using SFT and GRPO

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

This repository showcases hands-on projects leveraging distributed multi-GPU training to fine-tune large language models (LLMs).

Fully Sharded Data Parallel (FSDP) implementation of Transformer XL