FineTune
What It Really Takes to Fine-Tune a LLM Model for a Real-World Use Case
Imagine you’re leading an AI initiative at a mid-sized healthcare startup. Your team has prototyped a patient-facing chatbot that helps summarize diagnoses and explain treatment options using a large language model. The demo went well — the investors are thrilled, and leadership wants it in production. But one week into “real-world testing,” you’re staring at…
A Step-by-Step Coding Guide to Efficiently Fine-Tune Qwen3-14B Using Unsloth AI on Google Colab with Mixed Datasets and LoRA Optimization
Fine-tuning LLMs often requires extensive resources, time, and memory, challenges that can hinder rapid experimentation and deployment. Unsloth AI revolutionizes this process by enabling fast, efficient fine-tuning state-of-the-art models like Qwen3-14B with minimal GPU memory, leveraging advanced techniques such as 4-bit quantization and LoRA (Low-Rank Adaptation). In this tutorial, we walk through a practical implementation…