sagar-kc7/tinyllama-alpaca-unsloth

TinyLlama Alpaca — Unsloth Fine-tuning Practice

Overview

This is a practice fine-tune of TinyLlama-1.1B on the Alpaca dataset using Unsloth. The goal of this project was not to achieve state-of-the-art performance but to understand the end-to-end fine-tuning pipeline using Unsloth, LoRA, and SFTTrainer on Google Colab.

What I learned

• Setting up Unsloth for memory-efficient fine-tuning on Colab T4 GPU
• Configuring LoRA parameters (rank, alpha, target modules)
• Formatting datasets using the Alpaca instruction template
• Using SFTTrainer from the trl library
• Saving and pushing LoRA adapters to HuggingFace Hub

Training Details

Setting	Value
Base model	unsloth/tinyllama-bnb-4bit
Dataset

Uploaded model

• Developed by: sagar-kc7
• License: apache-2.0
• Finetuned from model : unsloth/tinyllama-bnb-4bit

This llama model was trained 2x faster with Unsloth