🧠 Fine-Tuning Qwen 2.5-3B Instruct with LoRA on T4 GPU

This project demonstrates efficient fine-tuning of Qwen 2.5-3B Instruct, a powerful LLM by Alibaba, using LoRA (Low-Rank Adaptation) and the Unsloth framework. It is optimized for low-cost GPUs like NVIDIA T4, using 4-bit quantization to reduce memory footprint.

---

🚀 Project Goals

• Fine-tune Qwen 2.5-3B efficiently on consumer-grade hardware (T4 GPU).
• Utilize LoRA for parameter-efficient tuning.
• Apply Unsloth’s optimized training engine for faster training and inference.
• Enable support for long-context reasoning and instruction-following tasks.
• Keep the solution simple, modular, and compatible with Colab or Kaggle environments.

---