How to Fine-Tune an LLM (Supervised Fine-Tuning / SFT) – Complete Tutorial
How to Fine-Tune an LLM (Supervised Fine-Tuning / SFT) – Complete Tutorial
In this video, we explain Supervised Fine-Tuning (SFT) for Large Language Models (LLMs) and walk through a complete step-by-step implementation.
You’ll learn:
• What supervised fine-tuning is
• How SFT differs from pretraining and RLHF
• How to fine-tune an LLM using real data
• Code walkthrough with practical implementation
This tutorial is ideal for ML engineers, AI researchers, and anyone learning LLM training.
🔗 Colab Notebook:
[https://colab.research.google.com/dri...]
Topics Covered:
LLM training pipeline
Instruction tuning
Loss functions in SFT
Dataset formatting
Practical fine-tuning workflow
Keywords:
supervised fine tuning, fine tune LLM, LLM training tutorial, SFT explained, LLM implementation, HuggingFace fine tuning
00:00 Introduction
02:10 What is Supervised Fine-Tuning?
06:45 Pretraining vs SFT vs RLHF
11:30 Dataset Formatting
15:20 Training Loop Explained
21:10 Code Walkthrough
26:00 Key Takeaways
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Let me know what paper or technique I should explain next 👇