Spaces:
Running on Zero
Running on Zero
| 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 | |