Fine-tuning TinyLlama with custom Medical dataset for Beginners |  HuggingFace | TinyLlama

In this hands-on tutorial, we'll dive into fine-tuning TinyLlama for medical text dialogue conversational AI application  What you'll learn Setting up TinyLlama for medical domain adaptation Implementing fine-tuning with minimal computing resources Understanding Weights & Biases integration for training monitoring Working with practical batch sizes and gradient accumulation - Real-world considerations and optimization strategies ⭐️ Timeline ⭐️ 00:00 : Step-by-step code walkthrough - Llama 8B model - HF TinyLLama 03:46 : HF TinyLlama and Lora adaptation for Resource-conscious training approach 12:20 : Data preparation and Finetuning 21:12 : Parameter optimization for optimal performance 23:21 : Save the model, push to HuggingFace and test the finetuned-model 26:51 : Conclusion 📌 Notebook: https://www.kaggle.com/code/aboniasoj... 📌 Or find the notebook here: https://github.com/Abonia1/LLM-Finetu... 📌 Dataset: https://huggingface.co/datasets/rusla... 📌 Fine-tuned model in HF: Abonia/tinyllama-medical-chat Note: This tutorial focuses on educational concepts using minimal resources. Production deployment would require additional optimization. Planned for Llama 8B fientunig as because my request to use this model is still in progress so Meantime we will fine tune TinyLlama chat model. ___________________________________________________________________________ 🔔 Get our Newsletter and Featured Articles: https://abonia1.github.io/newsletter/ 🔗 Linkedin:   / aboniasojasingarayar   🔗 Find me on Github: https://github.com/Abonia1 🔗 Medium Articles:   / abonia   #LLM # finetuning #MachineLearning #AI #TinyLlama #MedicalAI #Tutorial #Python #LLM