pipeline_tag: text-to-image
widget:
- text: >-
movie scene screencap, cinematic footage. thanos smelling a little yellow
rose. extreme wide angle,
output:
url: 1man.png
- text: 'A tiny robot taking a break under a tree in the garden '
output:
url: robot.png
- text: mystery
output:
url: mystery.png
- text: a cat wearing sunglasses in the summer
output:
url: cat.png
- text: 'robot holding a sign that says ’a storm is coming’ '
output:
url: storm.png
- text: >-
The Exegenesis of the soul, captured within a boundless well of starlight,
pulsating and vibrating wisps, chiaroscuro, humming transformer
output:
url: soul.png
- text: >-
Lady of War, chique dark clothes, vinyl, imposing pose, anime style, 90s
natural photography of a man, glasses, cinematic,
output:
url: anime.png
- text: natural photography of a man, glasses, cinematic,
output:
url: glasses.png
- text: if I could turn back time
output:
url: time.png
- Prompt
- movie scene screencap, cinematic footage. thanos smelling a little yellow rose. extreme wide angle,
- Prompt
- god
- Prompt
- A tiny robot taking a break under a tree in the garden
- Prompt
- mystery
- Prompt
- a cat wearing sunglasses in the summer
- Prompt
- robot holding a sign that says ’a storm is coming’
- Prompt
- The Exegenesis of the soul, captured within a boundless well of starlight, pulsating and vibrating wisps, chiaroscuro, humming transformer
- Prompt
- anime boy, protagonist, best quality
- Prompt
- natural photography of a man, glasses, cinematic,
- Prompt
- if I could turn back time
- Prompt
- ("Mobius" text logo) powerful aura, swirling power, cinematic
- Prompt
- the backrooms
Mobius: Redefining State-of-the-Art in Debiased Diffusion Models
Mobius, a revolutionary diffusion model, pushes the boundaries of domain-agnostic debiasing and representation realignment. By employing the cutting-edge constructive deconstruction framework, Mobius achieves unrivaled generalization across a vast array of styles and domains, eliminating the need for expensive pretraining from scratch.
Surpassing the State-of-the-Art
Mobius outperforms existing state-of-the-art diffusion models in several key areas:
Unbiased generation: Mobius generates images that are virtually free from the inherent biases commonly found in other diffusion models, setting a new benchmark for fairness and impartiality across all domains. Exceptional generalization: With its unparalleled ability to adapt to an extensive range of styles and domains, Mobius consistently delivers top-quality results, surpassing the limitations of previous models. Efficient fine-tuning: The Mobius base model serves as a superior foundation for creating specialized models tailored to specific tasks or domains, requiring significantly less fine-tuning and computational resources compared to other state-of-the-art models.
Groundbreaking Performance
Mobius has been rigorously tested across an unparalleled variety of prompts, consistently demonstrating its exceptional performance in numerous scenarios:
Generating photorealistic images of people, animals, and objects with an unprecedented level of detail and accuracy Creating breathtaking artwork in a wide spectrum of styles, from classic paintings to cutting-edge digital art, surpassing the quality and diversity of existing models Producing highly detailed and precise visualizations of complex scientific concepts and data, enabling new possibilities for research and education
Collaborative Evolution
We invite the community to contribute to the ongoing development of Mobius, helping to shape the future of debiased diffusion models. Please refer to our contribution guidelines for more information on how to get involved.
Usage and Recommendations
- a CFG of either 3.5 or 7.0
- Requires a CLIP skip of -3
- highly suggested to preappenmed watermark to all negatives and keep negatives simple such as "watermark" or "worst, watermark"
This model supports and encourages experimentation with various tags, offering users the freedom to explore their creative visions in depth.
License
refer to the file named License in this repo.