---
language:
- en
license: creativeml-openrail-m
thumbnail: "https://huggingface.co/Guizmus/SDArt_ChaosAndOrder768/resolve/main/showcase.jpg"
tags:
- stable-diffusion
- text-to-image
- image-to-image
---
# SDArt : Chaos And Order (version based on 2.1 768px)

![Showcase](https://huggingface.co/Guizmus/SDArt_ChaosAndOrder768/resolve/main/showcase.jpg)

## Theme

> The storm was a maelstrom of darkness and red, a tempest of writhing fury that threatened to swallow everything in its path. Against this chaos stood the ordered landscape, an unwavering bastion of precision and clarity, holding back the furious assault. The battle raged on, each side locked in an unforgiving struggle for dominance.
> Amidst Chaos & Order, a figure emerged. A young girl with eyes that glowed like the sun stood tall and unafraid as the battle unfolded. With a calm determination, she held out her hands and began to guide the energies around her. The forces of Chaos & Order clashed and collided, lightning bolts and sharp lines slashing through the air with reckless abandon. But the girl remained unflinching, her movements fluid and precise as she weaved her way through the tumultuous battlefield.
> The opposing forces began to merge as swirling clouds of Chaos began to dissipate, softening into curves and patterns that blended seamlessly with the structured landscape of Order. The sky bloomed into a tapestry of colors, a reflection emerging forth from two opposites. 
> In the end, it was neither Chaos or Order that prevailed, but the harmony that emerged from their interplay. And the young girl, with her eyes shining like stars, knew that this was the true power of Balance.

💢 Two forces, one outcome. Chaos and Order clash in a visually stunning battle for dominance! 🔳 

*Encapsulate the tension between chaos and order in a dynamic, visually striking composition. The human experience of the push-pull struggle between two powerful forces.*

**Challenges:**

* Use contrasting colors and shapes to create a sense of conflict between two or more opposing forces.
* At least one aspect that represents Chaos and one aspect that represents Order.
* Create a sense of movement and energy that captures the dynamic interplay between Chaos & Order.


## Model description 

This is a model related to the "Challenge of the WeekEnd" contest on [Stable Diffusion discord](https://discord.gg/stablediffusion).

I try to make a model out of all the submission for people to continue enjoy the theme after the even, and see a little of their designs in other people's creations. The token stays "SDArt" and I balance the learning on the low side, so that it doesn't just replicate creations.

The total dataset is made of 22 pictures. It was trained on [Stable diffusion 2.1 768px](https://huggingface.co/stabilityai/stable-diffusion-2-1). I used [EveryDream](https://github.com/victorchall/EveryDream2trainer) to do the training, 100 total repeat per picture. The pictures were tagged using the token "SDArt", and an arbitrary token I choose. The dataset is provided below, as well as a list of usernames and their corresponding token.

The recommended sampling is k_Euler_a or DPM++ 2M Karras on 20 steps, CFGS 7.5 .

[The model is also available here](https://huggingface.co/Guizmus/SDArt_ChaosAndOrder) in a version trained on 1.5 as a base.

## Trained tokens

* SDArt
* rcn
* in 
* aten
* opi
* omd
* kuro
* nlwx
* asot
* psst
* buka
* muc
* kts
* utm
* avel
* mss
* guin
* pgs
* crit
* mlas
* phol
* dds
* pte
* rean

## Download links

[SafeTensors](https://huggingface.co/Guizmus/SDArt_ChaosAndOrder768/resolve/main/SDArt_ChaosAndOrder768.safetensors)

[CKPT](https://huggingface.co/Guizmus/SDArt_ChaosAndOrder768/resolve/main/SDArt_ChaosAndOrder768.ckpt)

[Config (yaml)](https://huggingface.co/Guizmus/SDArt_ChaosAndOrder768/resolve/main/SDArt_ChaosAndOrder768.yaml)

[Dataset](https://huggingface.co/Guizmus/SDArt_ChaosAndOrder768/resolve/main/dataset.zip)

## 🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information,
please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion).

You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX]().

```python
from diffusers import StableDiffusionPipeline
import torch

model_id = "Guizmus/SDArt_ChaosAndOrder768"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "SDArt mlas"
image = pipe(prompt).images[0]

image.save("./SDArt.png")
```