LLM Fine tuning Interview Questions and Answers | AI Engineer | Data Scientist | ML Engineer скачать в хорошем качестве

LLM Fine tuning Interview Questions and Answers | AI Engineer | Data Scientist | ML Engineer

🚀 Master LLM Fine-Tuning and Prompt Engineering 🔗 Project Link: https://www.kaggle.com/code/paultimot... In this video, we dive deep into the world of Large Language Model (LLM) fine-tuning and instruction fine-tuning to elevate your AI skills. Whether you're just starting or looking to refine your techniques, this guide is for you. 🧠 What You'll Learn: Instruction Fine-Tuning: How to customize LLMs for specific use cases. Prompt Engineering Essentials: Zero-shot learning One-shot learning Few-shot learning Chain of Thought (CoT) reasoning for enhanced outcomes Parameter-Efficient Fine-Tuning (PEFT): LoRA (Low-Rank Adaptation) Adapters for lightweight and efficient fine-tuning Reinforcement Learning from Human Feedback (RLHF): The key to building more aligned and robust models. https://chatgpt.com/share/68d37999-77... techniques. Timestamp: 0:00 Types of LLM Finetuning 01:04 Prompt engineering techniques 03:33 PEFT QLORA 12:25 Instruction Finetuning & RLHF 📌 Don't forget to like, share, and subscribe for more deep dives into AI and machine learning! #LLMFineTuning #PromptEngineering #InstructionFineTuning #PEFT #RLHF #genai