unsloth-qlora

Community

Extreme VRAM efficiency for LLM fine-tuning.

Authorcuba6112
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill addresses the significant VRAM limitations encountered when fine-tuning large language models, enabling powerful training on consumer-grade hardware.

Core Features & Use Cases

  • 4-bit Quantization: Utilizes Unsloth's dynamic 4-bit quantization to drastically reduce VRAM usage.
  • High Accuracy Preservation: Maintains accuracy comparable to full fine-tuning by selectively preserving critical weights.
  • Use Case: Fine-tune a 70B parameter model on a single 24GB GPU, achieving performance close to full fine-tuning without requiring enterprise-level hardware.

Quick Start

Load a 70B parameter model using the unsloth-qlora skill with 4-bit quantization enabled.

Dependency Matrix

Required Modules

unslothbitsandbytesaccelerate

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: unsloth-qlora
Download link: https://github.com/cuba6112/skillfactory/archive/main.zip#unsloth-qlora

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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