---
title: SDXL Model Merger
emoji: 🐢
colorFrom: green
colorTo: purple
sdk: gradio
sdk_version: 6.9.0
python_version: '3.12'
app_file: app.py
pinned: false
license: mit
short_description: Merge SDXL checkpoints & LoRA and export with quantization
---

# SDXL Model Merger

A Gradio-based web application for merging, generating with, and exporting Stable Diffusion XL (SDXL) checkpoints.

## Features

- **Load pipelines** from HuggingFace URLs with optional VAE and multiple LoRAs
- **Generate images** with seamless tiling support for panoramic/360° outputs
- **Export merged models** with quantization options (int8, int4, float8)

## Usage on HuggingFace Spaces

This app is optimized for both local and Space deployments:

```bash
# Local deployment
python app.py

# Space deployment with CPU fallback
export DEPLOYMENT_ENV=spaces
python app.py
```

For best results:
- Use **GPU** (NVIDIA) for fast generation - ~8GB VRAM recommended
- CPU mode is available but will be slower and use more RAM (~16GB+)

## Requirements

- Python 3.10+
- PyTorch 2.0+
- 4GB+ VRAM (GPU) or 16GB+ RAM (CPU)
- ~2GB disk space for cached models