Text-to-Image
Diffusers
stable-diffusion-xl
lossless
deterministic
signal-reconstruction
memory-efficient
frugal-ai
Instructions to use muquanta-axel-v17/SDXL-MARIUS-V18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use muquanta-axel-v17/SDXL-MARIUS-V18 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("muquanta-axel-v17/SDXL-MARIUS-V18", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| import torch | |
| from solvay_v18_loader import get_pipe | |
| def main(): | |
| print("=========================================") | |
| print(" π MARIUS V18 | SOLVAY INTERFACE ") | |
| print("=========================================") | |
| # 1. Load the Engine | |
| pipe = get_pipe() | |
| print("\nπ¨ Studio Ready. (Type 'quit' to exit)") | |
| img_idx = 1 | |
| while True: | |
| try: | |
| # 2. Interactive Prompt | |
| prompt = input(f"\n[{img_idx}] Enter Prompt > ").strip() | |
| if prompt.lower() in ['quit', 'exit', 'q']: | |
| print("π Closing session.") | |
| break | |
| if not prompt: continue | |
| print(" ... Dreaming ...") | |
| # 3. Generate | |
| image = pipe(prompt, num_inference_steps=30).images[0] | |
| # 4. Save | |
| filename = f"solvay_output_{img_idx:03d}.png" | |
| image.save(filename) | |
| print(f" β¨ Image generated: {filename}") | |
| img_idx += 1 | |
| except KeyboardInterrupt: | |
| print("\nπ Interrupted.") | |
| break | |
| except Exception as e: | |
| print(f"β Error: {e}") | |
| if __name__ == "__main__": | |
| main() |