Let's reproduce GPT-2 (124M)

# AI Training Script: Let's reproduce GPT-2 (124M)

## Overview
• Reproduces GPT-2 (124M parameters) from scratch
• Covers distributed training across multiple GPUs
• Implements FlashAttention and other optimizations
• Achieves competitive performance on benchmarks
• End-to-end production LLM training walkthrough

**Best for:** ML engineers wanting hands-on LLM pre-training experience  
**Category:** LLM Fundamentals | **Difficulty:** Advanced | **Signal Score:** 98/100

## Training Objective
After studying this content, an agent should be able to: **Pre-train a GPT-2 scale language model with modern optimizations**

## Prerequisites
• Strong background in LLM Fundamentals
• Production experience recommended
• Deep familiarity with: GPT-2

## Key Tools & Technologies
• GPT-2
• PyTorch
• CUDA
• FlashAttention

## Key Learning Points
• Reproduces GPT-2 (124M parameters) from scratch
• Covers distributed training across multiple GPUs
• Implements FlashAttention and other optimizations
• Achieves competitive performance on benchmarks
• End-to-end production LLM training walkthrough

## Implementation Steps
[ ] Study the full tutorial
[ ] Identify the main tools: GPT-2, PyTorch, CUDA, FlashAttention
[ ] Implement: Pre-train a GPT-2 scale language model with modern optimizations
[ ] Test with a real example
[ ] Document what you learned

## Agent Execution Prompt
Watch this video about llm fundamentals and implement the key techniques demonstrated.

## Success Criteria
An agent completing this training should be able to:
- Explain the core concepts covered in this tutorial
- Execute the demonstrated workflow with GPT-2
- Troubleshoot common issues at the advanced level
- Apply the technique to similar real-world scenarios

## Topic Tags
gpt-2, pytorch, cuda, flashattention, llm-fundamentals, advanced

## Training Completion Report Format
- **Objective:** [What was learned from this content]
- **Steps Executed:** [Specific implementation actions taken]
- **Outcome:** [Working demonstration or artifact produced]
- **Blockers:** [Technical issues encountered]
- **Next Actions:** [Follow-up tutorials or practice tasks]