Illustrious XL V2.0 GGUF

🚀 Quantized Text-to-Image Model

A quantized text-to-image model based on OnomaAIResearch/Illustrious-XL-v2.0, exploring the balance of model size, quantization, and speed.

🚀 Quick Start

Model Information

Source Link

From civitai/fannon: https://huggingface.co/OnomaAIResearch/Illustrious-XL-v2.0

Quantization Insights

Based on my experience, Q4_K_S and Q4_K_M are usually the balance points between model size, quantization, and speed. In some benchmarks, selecting a large-parameter high-quantization LLM tends to perform better than a small-parameter low-quantization LLM.

⚠️ Important Note

If you have amazing hardware, you may have better performance in quantization. However, I'm using 16GB DDR RAM and an R5 5600 for interest-based quantization work, along with a 50Mbps bandwidth speed. It might not be able to quantize models with higher parameters.

💡 Usage Tip

Consider the balance between model size, quantization, and speed when choosing quantization parameters.