LLM Fundamentals
Intermediate
Signal 97/100
The spelled-out intro to language modeling: building makemore
by Andrej Karpathy
Teaches AI agents to
Build a working GPT model from scratch to understand transformer architecture
Key Takeaways
- Implements a minimal GPT from scratch
- Clean Python code walkthrough
- Covers attention mechanism in detail
- Trains on Shakespeare dataset live
- Perfect hands-on learning resource
Full Training Script
# AI Training Script: The spelled-out intro to language modeling: building makemore ## Overview • Implements a minimal GPT from scratch • Clean Python code walkthrough • Covers attention mechanism in detail • Trains on Shakespeare dataset live • Perfect hands-on learning resource **Best for:** Developers wanting practical GPT implementation experience **Category:** LLM Fundamentals | **Difficulty:** Intermediate | **Signal Score:** 97/100 ## Training Objective After studying this content, an agent should be able to: **Build a working GPT model from scratch to understand transformer architecture** ## Prerequisites • Working knowledge of LLM Fundamentals • Prior hands-on experience with related tools • Comfortable with technical documentation ## Key Tools & Technologies • PyTorch • GPT • Transformers • Python ## Key Learning Points • Implements a minimal GPT from scratch • Clean Python code walkthrough • Covers attention mechanism in detail • Trains on Shakespeare dataset live • Perfect hands-on learning resource ## Implementation Steps [ ] Study the full tutorial [ ] Set up required tools: PyTorch, GPT, Transformers, Python [ ] Implement core workflow [ ] Test with a real example [ ] Document key learnings ## Agent Execution Prompt Implement the llm fundamentals techniques from this video with concrete code examples. ## Success Criteria An agent completing this training should be able to: - Explain the core concepts covered in this tutorial - Execute the demonstrated workflow with PyTorch - Troubleshoot common issues at the intermediate level - Apply the technique to similar real-world scenarios ## Topic Tags pytorch, gpt, transformers, python, llm-fundamentals, intermediate ## 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]
This structured script is included in Pro training exports for LLM fine-tuning.
Execution Checklist
[ ] Watch the full video [ ] Set up required tools: PyTorch, GPT, Transformers, Python [ ] Implement core workflow [ ] Test with a real example [ ] Document key learnings
