README.md

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    score_9, score_8_up, score_7_up, score_6_up, score_5_up, score_4_up, Vegeta, iconic Saiyan prince from DBZ, (powerful stance:1.3), (muscle definition:1.2), in mid-battle roar, (Super Saiyan transformation:1.5), crackling aura of energy enveloping him, dynamic background showcasing a devastated battlefield reminiscent of Namek or Earth during epic confrontations; elements of Akira Toriyama's signature art style blended seamlessly with high saturation and bold lines to capture the intensity and raw power synonymous with Dragon Ball Z; dramatic lighting casting strong shadows to enhance Vegeta's chiseled features and battle torn armor; camera angle low and looking up to emphasize his dominance and unyielding spirit. 
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license: gpl-3.0
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<Gallery />


## Introducing Proteus-RunDiffusion

https://discord.gg/EDQD3Zpwvc
In the development of Proteus-RunDiffusion, our team embarked on an exploratory project aimed at advancing the capabilities of AI in art creation. Our journey, inspired by the broad achievements of models like Pony Diffusion v6 XL CLIP, led us to experiment with the CLIP architecture in novel ways. Through a serendipitous process of trial, error, and discovery, we developed a unique approach to retraining CLIP that we hadn't initially set out to achieve. This approach inadvertently unlocked new potentials in character recognition, natural language processing, and, most notably, the versatility of artistic expression.


https://rundiffusion.com/proteus-rundiffusion#view-generation-samples

The cornerstone of our discovery, which we refer to as "style unlocking," emerged unexpectedly. This breakthrough allows models that were previously limited to specific genres or styles, such as anime, to generate art across a broader spectrum, including high-fidelity photorealism. This was a result of our reimagined CLIP model's ability to interpret and understand prompts in ways that surpass the original boundaries of style and genre.


We have observed that this retraining has also led to significant improvements in handling CFG scaling, effectively broadening the range from 3 to 50 without the previous limitations or failures. This enhancement opens up new avenues for creative expression and technical reliability in AI-generated art.


In terms of usage, we recommend a CLIP setting of -2 along with a strategic use of light negatives for optimizing the artistic output of Proteus-RunDiffusion. The CFG setting can vary depending on the project, with 8.5 being ideal for standard requests and 3.5 for more artistic explorations. The model supports and encourages experimentation with various tags, offering users the freedom to explore their creative visions in depth.

Using Proteus-RunDiffusion: Expect a Different Experience

When you start using Proteus-RunDiffusion, be ready for it to behave differently from other AI art models you've used. It's been designed in a unique way, which means it will respond to your prompts and commands in its own style. This difference is part of what makes it special, but it also means there's a learning curve. You'll need some time to get familiar with how it works and what it can do. So, as you begin, keep an open mind and be prepared to adjust your approach.


Importantly, we want to clarify that our development of Proteus-RunDiffusion was inspired by existing works but does not directly incorporate or rework specific components from models like Pony Diffusion's CLIP. Our advancements are the result of our proprietary research and development efforts, aimed at enhancing the creative possibilities and compatibility across different AI art generation platforms.




There will be a upcoming Human Preference Study and Research Publication
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