LLM Fine-Tuning 11: LLM Knowledge Distillation | How to Distill LLMs (LLAMA, Phi & Beyond) Part 2

In this video (Part 2 of our Fine-Tuning Series), we dive into LLM Knowledge Distillation—a powerful way to make Large Language Models (LLMs) like BERT, DistilBERT, Phi, and LLaMA smaller, faster, and cheaper to run without losing too much performance. You’ll learn: What Knowledge Distillation is and why it matters for LLMs How Teacher-Student training works (with Hugging Face Transformers) A hands-on DistilBERT distillation example using PyTorch & Hugging Face How to apply these concepts to other models like LLaMA and custom LLMs Tips to speed up inference, cut costs, and deploy on edge devices Perfect for: ML Engineers Data Scientists Students & Researchers Anyone building with LLMs in 2025! Code Repository & Notes: https://github.com/sunnysavita10/Complete-LLM-Finetuning/blob/main/BERT_Finetuning.ipynb Got questions or topic requests? Drop a comment below 👇. 🔔 Subscribe for more AI tutorials 📢 Like 👍 | Comment 💬 | Subscribe 🔔 for more LLM power content! 📌 Keywords Covered: #LLMFineTuning #RNNvsTransformer #AITransformers #DeepLearning #NeuralNetworks #FineTuningExplained #TransformerRevolution #LLMSeries #MLTutorials #Finetuning #RAG #AIAgents #LLMWorkflow #AIForBusiness #LLMComparison #LangChain #OpenAI #EnterpriseAI #PromptEngineering #HuggingFace #LLMTutorial #SunnyAI #Transformers2025 Drop your questions/suggestions in the comments—let’s build this together! Don't miss out; learn with me! LLM Fine-Tuning Material: https://github.com/sunnysavita10/Complete-LLM-Finetuning #langchain LangGraph #AIagents #StructuredOutput #GenerativeAI #LangChain #AIautomation #llm #embedding #ai #futureai #generativeai #genai #textgeneration #ragapp #langchain #programminglogic #python #chatbot #openai #gpt #langchainj #rag #crossencoder #transformers #multiretriever #ragfusion #advancerag #llamaindex #langchain #gemini #google #rag #LCEL #langgraph #aiagent #react #aiagents #aiagents #agenticAI #generativeai #doctorappointment #automation #AI #M