Uploaded March 2026 | Updated September 2026, 2 weeks ago
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
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Fine-tuning a 70 billion parameter model requires over 140GB of VRAM - hardware that most engineers simply cannot access. Yet this is one of the most asked fine-tuning questions in AI Engineer and GenAI interviews at FAANG, MNCs, and top Indian startups in 2026. In this video, we break down LoRA vs QLoRA in a structured interview Q&A format so you can answer this with full confidence and depth.
We cover why full fine-tuning is too expensive for most use cases, how LoRA reduces memory by training only small low-rank matrices while keeping original weights frozen, how QLoRA goes one step further by quantizing base model weights to 4-bit precision to run a 70B model on a single GPU, and a direct side-by-side comparison across memory, speed, accuracy, and GPU requirements. Every section gives you the exact strong answer you should deliver in your next interview.
If you are preparing for AI Engineer, ML Engineer, or GenAI roles in 2026 - or actively building fine-tuned LLM applications using Unsloth, HuggingFace, or Ollama - this is a must-watch before your interview.
Watch the full Gen AI Interview 2026 Preparation Guide playlist here:
youtube.com/playlist?list=PLc2rvfiptPSQdF1F23_6OAemHVhy-CAun
📚 Learn More with My Udemy Courses
🧠 Master OpenAI Agent Builder - Deploy Chatbot to Your Website
udemy.com/course/master-openai-agent-builder-low-code-ai-projects-workflow/?referralCode=B0B67D18B1013E488FB7
🔥 MCP Mastery: Build AI Apps with Claude, LangChain and Ollama
udemy.com/course/mcp-mastery-build-ai-apps-with-claude-langchain-and-ollama/?referralCode=31C17C306A59601B8689
🚀 Agentic RAG with LangChain & LangGraph
udemy.com/course/agentic-rag-with-langchain-and-langgraph/?referralCode=C0BCC208F53AF2C98AC5
🧠 LangGraph with Ollama
udemy.com/course/langgraph-with-ollama/?referralCode=B646DCB44A189BEBC20C
⚡ Ollama and LangChain
udemy.com/course/ollama-and-langchain/?referralCode=7F4C0C7B8CF223BA9327
🔧 Fine-Tuning LLM with Hugging Face Transformers
udemy.com/course/fine-tuning-llm-with-hugging-face-transformers/?referralCode=6DEB3BE17C2644422D8E
📖 NLP with BERT in Python
udemy.com/course/nlp-with-bert-in-python/?referralCode=063516494616C76907CD
🌐 Connect with Me
Website & Blogs: kgptalkie.com
LinkedIn: linkedin.com/in/laxmimerit
GitHub: github.com/laxmimerit
Twitter (X): twitter.com/laxmimerit
📌 Support the Channel
👍 Like the video if it helps you
💬 Comment your doubts & feedback
🔔 Subscribe for free weekly AI & Data Science content
#DataScience #MachineLearning #LangChain #LangGraph #Ollama #Python #AI #DeepLearning #NLP #GenerativeAI #LLM #HuggingFace #BERT
🚀 The LangChain 10 Days FREE Bootcamp is live: 10 lessons, free AI models only, from your first API call to a production grade RAG agent. Start with Day 0 for the roadmap and setup.
📺 Full playlist: youtube.com/watch?v=KJ3_NExk7-Q&list=PLW4pPr9JCovI&index=1
----------
Fine-tuning a 70 billion parameter model requires over 140GB of VRAM - hardware that most engineers simply cannot access. Yet this is one of the most asked fine-tuning questions in AI Engineer and GenAI interviews at FAANG, MNCs, and top Indian startups in 2026. In this video, we break down LoRA vs QLoRA in a structured interview Q&A format so you can answer this with full confidence and depth.
We cover why full fine-tuning is too expensive for most use cases, how LoRA reduces memory by training only small low-rank matrices while keeping original weights frozen, how QLoRA goes one step further by quantizing base model weights to 4-bit precision to run a 70B model on a single GPU, and a direct side-by-side comparison across memory, speed, accuracy, and GPU requirements. Every section gives you the exact strong answer you should deliver in your next interview.
If you are preparing for AI Engineer, ML Engineer, or GenAI roles in 2026 - or actively building fine-tuned LLM applications using Unsloth, HuggingFace, or Ollama - this is a must-watch before your interview.
Watch the full Gen AI Interview 2026 Preparation Guide playlist here:
youtube.com/playlist?list=PLc2rvfiptPSQdF1F23_6OAemHVhy-CAun
📚 Learn More with My Udemy Courses
🧠 Master OpenAI Agent Builder - Deploy Chatbot to Your Website
udemy.com/course/master-openai-agent-builder-low-code-ai-projects-workflow/?referralCode=B0B67D18B1013E488FB7
🔥 MCP Mastery: Build AI Apps with Claude, LangChain and Ollama
udemy.com/course/mcp-mastery-build-ai-apps-with-claude-langchain-and-ollama/?referralCode=31C17C306A59601B8689
🚀 Agentic RAG with LangChain & LangGraph
udemy.com/course/agentic-rag-with-langchain-and-langgraph/?referralCode=C0BCC208F53AF2C98AC5
🧠 LangGraph with Ollama
udemy.com/course/langgraph-with-ollama/?referralCode=B646DCB44A189BEBC20C
⚡ Ollama and LangChain
udemy.com/course/ollama-and-langchain/?referralCode=7F4C0C7B8CF223BA9327
🔧 Fine-Tuning LLM with Hugging Face Transformers
udemy.com/course/fine-tuning-llm-with-hugging-face-transformers/?referralCode=6DEB3BE17C2644422D8E
📖 NLP with BERT in Python
udemy.com/course/nlp-with-bert-in-python/?referralCode=063516494616C76907CD
🌐 Connect with Me
Website & Blogs: kgptalkie.com
LinkedIn: linkedin.com/in/laxmimerit
GitHub: github.com/laxmimerit
Twitter (X): twitter.com/laxmimerit
📌 Support the Channel
👍 Like the video if it helps you
💬 Comment your doubts & feedback
🔔 Subscribe for free weekly AI & Data Science content
#DataScience #MachineLearning #LangChain #LangGraph #Ollama #Python #AI #DeepLearning #NLP #GenerativeAI #LLM #HuggingFace #BERT
