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
Update README.md
Browse filesupdated Empircical Benchmark Report Link to the 100+ pages report
https://huggingface.co/muquanta-axel-v17/SDXL-MARIUS-V18/resolve/main/Marius_V18_BenchmarkReport.pdf
README.md
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A rigorous side-by-side visual comparison verifying the lossless fidelity of the topological stabilization process is available in our full PDF report:
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A rigorous side-by-side visual comparison verifying the lossless fidelity of the topological stabilization process is available in our full PDF report:
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👉 **[Read the Empirical Benchmark Report (PDF)](https://huggingface.co/muquanta-axel-v17/SDXL-MARIUS-V18/resolve/main/Marius_V18_BenchmarkReport.pdf)**
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