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How to Fine-Tune Llama-3 on Your Own Dataset

A beginner-friendly guide to fine-tuning the powerful Llama-3 model on your custom data using Unsloth and Google Colab.

July 28, 20266 min read3,935 views
How to Fine-Tune Llama-3 on Your Own Dataset
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Why Fine-Tune?

While RAG is great for adding knowledge, fine-tuning is best for teaching a model a specific style, format, or tone (e.g., writing like your brand).

Using Unsloth

Unsloth makes fine-tuning 2x faster and uses 70% less VRAM. You can fine-tune an 8B model on a free Google Colab T4 GPU.

Preparing Your Data

Format your dataset into JSONL format using the ShareGPT or Alpaca format. Ensure high-quality examples, as LLMs amplify the quality of their training data.

Frequently Asked Questions

How much data do I need to fine-tune?+
You can see noticeable improvements in style and formatting with as few as 100-500 high-quality examples.

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