@hackproduct9: 🧠 Fine-tuning doesn’t teach your model new facts—it teaches new behavior. That’s the mental model that changed everything for me. When people say, “Let’s fine-tune the model with our documentation,” they’re usually solving the wrong problem. Use RAG when knowledge changes. Use fine-tuning when behavior should change. This diagram walks through the entire fine-tuning pipeline: 📚 Curate high-quality examples 🧹 Clean & tokenize the dataset 🎯 Choose Full Fine-Tune or LoRA/QLoRA 🔁 Train → Validate → Evaluate 🛡️ Run safety & quality checks 🚀 Version → Canary → Monitor in production The hardest part isn’t training the model. It’s creating a dataset that consistently demonstrates the behavior you want the model to learn. 📌 Save this as your end-to-end fine-tuning cheat sheet. #AI #FineTuning #LLM #GenerativeAI #MachineLearning
