LLM Fine tuning Interview Questions and Answers | AI Engineer | Data Scientist | ML Engineer
Автор: Crack AI ML Interviews
Загружено: 2025-01-26
Просмотров: 2194
Описание:
🚀 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
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