EASIEST Way to Train Custom Reasoning (CoT) Model - From Data Prep to Inference

Learn how to fine-tuning a reasoning model that can do chain of thought on the user query. We will use Camel-AI for building chain of thought dataset and unsloth for fine-tuning a small qwen model on the custom dataset. #finetuning #unsloth #chainofthought LINKS: Notebook: https://tinyurl.com/5n6nrreu dataset used: https://huggingface.co/datasets/zjrwtxtechstudio/o1data06 Unsloth website: https://unsloth.ai/ Camel-AI: https://www.camel-ai.org/ 💻 RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/courses/rag Let's Connect: 🦾 Discord: https://discord.com/invite/t4eYQRUcXB ☕ Buy me a Coffee: https://ko-fi.com/promptengineering |🔴 Patreon: https://www.patreon.com/PromptEngineering 💼Consulting: https://calendly.com/engineerprompt/consulting-call 📧 Business Contact: [email protected] Become Member: http://tinyurl.com/y5h28s6h 💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off). Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 00:00 Introduction to CoT fine-tuning 01:43 CoT dataset generation with Camel-AI 07:06 Fine-tuning with Unsloth 13:44 How the model performs All Interesting Videos: Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z