Complete LLM Fine Tuning Tutorial for Beginners (Free and Open Source) | Explained in Tamil | GenAI

🚀 Learn LLM Fine Tuning from Scratch (Tamil) | Complete GenAI Playlist Learn Large Language Model (LLM) Fine Tuning from scratch in Tamil through this complete end-to-end Generative AI playlist. This series is designed to help beginners and professionals understand how modern GenAI systems and open source LLMs work internally, and how to fine tune them for real world applications. This playlist explains LLM fundamentals, fine tuning strategies, and hands-on implementation using modern tools like Hugging Face, LoRA, PEFT, and Quantization. Every concept is explained step-by-step in simple Tamil with practical demonstrations, making it easy for developers and AI enthusiasts to follow along. Code Used: https://github.com/akash-balakrishnan... All Complete Tutorials for Beginners: RAG:    • 🔥 Complete RAG Tutorial 2025 in Tamil | Bu...   CrewAI Agents:    • 🔥 AI Agents Complete Tutorial for Beginner...   LangGraph Agents:    • 🔥 Complete LangGraph Tutorial in Tamil (Fr...   MCP:    • 🔥 Complete MCP Tutorial in Tamil - Build Y...   FastAPI:    • 🔥 Complete FastAPI Tutorial in Tamil - Bui...   Socials: 1:1 Mentorship : https://topmate.io/akash_balakrishnan... LinkedIn:   / akashb22   Instagram:   / ai.with.akash   📚 What You Will Learn 🧠 LLM Fundamentals What are Large Language Models (LLMs) How LLMs understand and generate text Encoding and decoding inside transformer models Tokenization and how text becomes tokens Understanding special tokens and tokenizers How attention mechanisms work in LLMs 🤖 Types of LLM Models Difference between Base LLM vs Instruct LLM What are Open Source LLMs vs Open Weights models Understanding popular open models like Llama, Mistral, and others Model formats such as GGUF and model quantization formats ⚙️ Fine Tuning Concepts What is LLM Fine Tuning When to use Fine Tuning vs RAG Dataset preparation for training LLMs Instruction datasets and conversation datasets Understanding Supervised Fine Tuning (SFT) 🧩 Efficient Fine Tuning Techniques Introduction to Parameter Efficient Fine Tuning (PEFT) How LoRA adapters work Training LLMs with low GPU memory Understanding Quantization techniques Running large models on limited hardware 🛠 Hands-On Implementation Preparing custom datasets for LLM training Implementing Fine Tuning using Hugging Face Training models with LoRA and PEFT Model evaluation techniques Testing the fine tuned model Publishing models to Hugging Face Hub 🧪 Real World AI Engineering Workflow Data preparation Model training pipeline Fine tuning strategies Model deployment Integrating models into applications 🎯 Who Should Watch This Playlist This series is perfect for: AI Engineers Machine Learning Engineers Data Scientists Software Developers GenAI Enthusiasts Students learning Artificial Intelligence Anyone who wants to build and fine tune their own LLM Even if you are a complete beginner, this playlist will help you understand how modern Generative AI systems are built and trained. 💡 Why This Playlist Is Different ✔ Explained entirely in Tamil for better understanding ✔ Covers theory + hands-on implementation ✔ Focus on real industry techniques used in GenAI ✔ Beginner friendly explanation of complex AI concepts ✔ Helps you prepare for AI Engineering and ML roles 🔔 What You Will Be Able To Do After This Series After completing this playlist you will be able to: Understand how Large Language Models work internally Fine tune open source LLMs Prepare training datasets Implement LoRA and PEFT based training Run models using quantization Deploy and publish models using Hugging Face 📌 Topics Covered LLM Basics Tokenization Special Tokens Base vs Instruct Models Open Source LLMs Fine Tuning Supervised Fine Tuning (SFT) LoRA PEFT Quantization GGUF Models Hugging Face Dataset Preparation Model Evaluation Generative AI Applications 🔎 Hashtags #LLMFineTuning #GenerativeAI #GenAI #TamilAI #LLM #LoRA #PEFT #Quantization #HuggingFace #OpenSourceLLM #RAG #MachineLearningTamil #AIEngineer #MLEngineer #DataScienceTamil #FineTuningLLM #AIForBeginners #LLMTutorial 00:00:00 - Introduction 00:12:30 - Models and Setup 00:22:18 - Stages in Building LLM 00:32:43 - Stages in Fine Tuning LLM 00:40:28 - Unsloth Basics 00:50:38 - Quantization 01:03:34 - Loading LLM 01:09:45 - Tokenizer 01:19:53 - Special Tokens 01:31:17 - Internal working of LLM 01:40:02 - Fine Tuning methods (LoRA, PEFT etc) 01:55:12 - PEFT Implementation 02:07:14 - Dataset Preparation 02:18:40 - Supervised Fine Tuning 02:33:20 - Evaluation and Pushing model to Hugging Face