distributed-llm-pretraining-torchtitan

Distribute LLM pretraining across multiple GPUs with torchtitan.

2|Updated Jun 8, 2026

Search Tags:#llm #fsdp #pretraining #torchtitan #h100 #4d parallelism

Ready to run

npx skills add https://github.com/vikrant-project/devil-agent-ai-platform --skill distributed-llm-pretraining-torchtitan-vikrant-project

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: distributed-llm-pretraining-torchtitan
Source: https://github.com/vikrant-project/devil-agent-ai-platform/tree/main/agent_core/optional-skills/mlops/torchtitan
Command: npx skills add https://github.com/vikrant-project/devil-agent-ai-platform --skill distributed-llm-pretraining-torchtitan-vikrant-project

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires torch>=2.6.0, torchtitan>=0.2.0, torchao>=0.5.0, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides scalable distributed pretraining for large language models on H100 GPUs using torchtitan with 4D parallelism, enabling high-performance training from 8 to 512+ GPUs.

Core Features & Use Cases

Distributed LLM Pretraining: Offers distributed pretraining of large language models on H100 GPUs with torchtitan's 4D parallelism.
Scalability: Supports training on a wide range of GPU counts, from 8 to over 500 GPUs.
4D Parallelism: Utilizes FSDP2, TP, PP, and CP for high-performance training.
Float8 Support: Provides support for Float8 training to maximize speedups on H100 GPUs.
Use Case: Ideal for organizations that require high-performance training of LLMs such as Llama 3.1, DeepSeek V3, or custom models.

Quick Start

Start the distributed pretraining process for a Llama 3.1 model on 8 GPUs with the following command:

CONFIG_FILE="./torchtitan/models/llama3/train_configs/llama3_8b.toml" ./run_train.sh

Frequently Asked Questions about distributed-llm-pretraining-torchtitan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I pretrain an LLM on multiple H100 GPUs using 4D parallelism?▼

To pretrain an LLM on H100 GPUs with 4D parallelism, use torchtitan to distribute training from 8 to 512+ GPUs via FSDP2, TP, PP, and CP.

What is the best way to scale Llama 3.1 pretraining across 8 GPUs?▼

The best way to scale Llama 3.1 pretraining across 8 GPUs is using torchtitan's distributed training script with a specified TOML config file.

Does torchtitan support Float8 training to speed up LLM pretraining on H100?▼

Yes, torchtitan supports Float8 training to maximize pretraining speedups specifically on H100 GPUs when scaling large language models.

Can I use FSDP2 and tensor parallelism together for distributed LLM pretraining?▼

Yes, you can use FSDP2 and tensor parallelism together, as torchtitan utilizes 4D parallelism combining FSDP2, TP, PP, and CP for high-performance scaling.

What dependencies do I need to run distributed LLM pretraining with torchtitan?▼

You need torch>=2.6.0, torchtitan>=0.2.0, and torchao>=0.5.0 installed on a Linux or MacOS system to run distributed LLM pretraining.