unsloth-quantization

What problem does it solve?

This Skill addresses the significant VRAM limitations encountered during LLM fine-tuning, enabling efficient training on consumer-grade GPUs.

Core Features & Use Cases

• Dynamic 4-bit Quantization: Reduces memory usage by up to 4x for model weights.
• FP8 Training: Accelerates training speed by up to 2x on compatible hardware.
• 8-bit Optimizers: Minimizes VRAM usage for optimizer states.
• Use Case: Fine-tune a large language model on a GPU with only 12GB of VRAM by leveraging Unsloth's quantization techniques, achieving faster training times without compromising accuracy.

Quick Start

Use the unsloth-quantization skill to recommend optimal quantization settings for your GPU.