Generative AI from Basic to Advance - LLM Fine-Tuning 19: Fine-Tune Any LLM with Axolotl 🔥 Low-Code YAML Based Training (No Heavy Coding)

In this video, you’ll learn how to fine-tune ANY Large Language Model (LLM) using Axolotl with a low-code, YAML-based workflow — no heavy coding required Axolotl is a powerful open-source framework built on top of Hugging Face that simplifies LLM fine-tuning, LoRA / QLoRA, SFT, DPO, RLHF, and multimodal training using a single YAML configuration file. What you’ll learn in this video: What Axolotl is and why it’s better than plain Hugging Face training How YAML-based low-code fine-tuning works Fine-tuning LLMs using LoRA & QLoRA Training models like LLaMA, Mistral, Qwen, Mixtral Dataset loading from local, Hugging Face Hub, and cloud Running Axolotl with Docker & GPU support Training, inference, and cleanup – end-to-end workflow Common errors & fixes (VRAM, tokenizer, dataset formats) Models Covered: LLaMA / LLaMA-3 Qwen / Qwen-Vision Mistral / Mixtral Any Hugging Face compatible LLM Why Axolotl? Low-code / No-code fine-tuning One YAML file for training + inference Built-in optimizations (Flash Attention, QLoRA, Multipack) Multi-GPU & Docker ready Industry-grade LLM training pipeline This video is perfect for: GenAI Engineers ML Engineers LLMOps / MLOps learners Anyone serious about LLM fine-tuning 00:00 – Introduction & Agenda 03:22 – What is Axolotl? 10:06 – Why config-driven training matters in Axolotl 14:31 – What Axolotl can do that Hugging Face alone cannot 28:38 – Training methods supported by Axolotl and documentation overview 37:50 – Difference between Core Hugging Face, Unsloth, LLaMA Factory, and Axolotl Material & Resources: https://github.com/sunnysavita10/Complete-LLM-Finetuning/tree/main/LLM%20Fine-Tuning-19-Axolotl 🔔 Like, Share & Subscribe to stay updated with the full LLM fine-tuning playlist. Got questions or topic requests? Drop a comment below 👇. 📌 Keywords Covered: #LLMFineTuning #LLMQuantization #GPTQ #PTQ #QAT #AWQ #GGUF #GGML #llamaCpp #DeepLearning #NeuralNetworkOptimization #Transformers #HuggingFace #LangChain #LangGraph #RAG #AdvancedRAG #AIAgents #AgenticAI #GenerativeAI #LLMTutorial #AIProjects #AIForDevelopers #TransferLearning #FineTuning #PretrainedModels #OpenSourceAI #LLM #MachineLearning #ArtificialIntelligence #AITutorial #Python #Chatbot #StructuredOutput #PromptEngineering #TextGeneration #Embedding #LLMWorkflow #SunnyAI #YouTubeLearning #AIautomation #AIForBusiness #EndToEndTutorial #LLMFineTuning #DomainSpecificLLM #HuggingFace #SunnySavita #AIProjects #LangChain #FineTuningTutorial #AIML #LoRA #QLoRA #AITraining #CustomLLM #PDFData #preference alignment #rlhf #dpo #ppo #rewardmodel #llamafactory #lora #unsloth #axolotl Multimodel RAG Playlist: https://www.youtube.com/watch?v=7CXJWnHI05w&list=PLQxDHpeGU14D6dm0rmAXhdLeLYlX2zk7p&pp=gAQBiAQB RAG detailed playlist: https://www.youtube.com/watch?v=wTVTkOb3SZc&list=PLQxDHpeGU14Blorx3Ps1eZJ4XvKET1_vx&pp=gAQBiAQB GenAI Foundation Playlist: https://www.youtube.com/watch?v=ajWheP8ZD70&list=PLQxDHpeGU14D7NiPgqxC9qhKkx4jMQcDk&pp=gAQBiAQB Connect with me on social media LinkedIn: https://www.linkedin.com/in/sunny-savita/ One-to-One Call: https://topmate.io/sunny_savita10 GitHub: https://github.com/sunnysavita10 Telegram: https://t.me/aimldlds