unsloth-lora

What problem does it solve?

This Skill addresses the challenge of fine-tuning large language models (LLMs) on hardware with limited VRAM by optimizing the Low-Rank Adaptation (LoRA) process.

Core Features & Use Cases

• 16-bit LoRA/rsLoRA: Enables efficient fine-tuning with reduced memory usage.
• Optimized Kernels: Accelerates training speed through specialized implementations.
• Rank-Stabilized LoRA: Improves stability for higher rank configurations.
• Use Case: Fine-tune a large LLM for a specific task on a consumer GPU, achieving performance comparable to full fine-tuning but with significantly less memory.

Quick Start

Configure LoRA parameters for Unsloth using the provided Python script, specifying rank and alpha values.