📘 Finetuning Large Language Models

By DeepLearning.AI

Welcome! 👋 This repository is for students and practitioners taking the Finetuning Large Language Models course offered by DeepLearning.AI.

The course explores how to adapt powerful foundation models to specialized tasks efficiently, responsibly, and with practical hands-on exercises.

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🚀 What You’ll Learn

• Introduction to LLMs – why and when finetuning is needed
• Parameter-Efficient Finetuning (PEFT) – techniques like LoRA and adapters
• Instruction Finetuning – aligning models for task-specific performance
• Evaluation & Safety – measuring effectiveness and mitigating risks
• Practical Walkthroughs – coding labs with Hugging Face & modern tools

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🛠️ Getting Started

1. Clone the Repository

git clone https://github.com/sdivyanshu90/Finetuning-Large-Language-Models.git
cd Finetuning-Large-Language-Models

2. Run the Labs

Open Jupyter notebooks:

jupyter notebook

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📚 Prerequisites

• Basic Python programming 🐍
• Familiarity with PyTorch or TensorFlow
• Understanding of transformers and Hugging Face libraries (helpful, but not mandatory!)

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🤝 Contributing

This repo is for learning purposes. If you’d like to fix a typo, improve instructions, or add resources, feel free to open a pull request. 🙌

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🙏 Acknowledgment

This course is created and provided by DeepLearning.AI. We are grateful for their mission to make cutting-edge AI education accessible worldwide.

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✨ Happy finetuning!