README.md

---
pipeline_tag: text-to-image
widget:
- text: >-
    Anime full body portrait of a swordsman holding his weapon in front of him. He is facing the camera with a fierce look on his face. Anime key visual (best quality, HD, ~+~aesthetic~+~:1.2)
  output:
    url: upscaled_image.png
- text: >-
    spacious,circular underground room,{dirtied and bloodied white tiles},amalgamation,flesh,plastic,dark fabric,core,pulsating heart,limbs,human-like arms,twisted angelic wings,arms,covered in skin,feathers,scales,undulate slowly,unseen current,convulsing,head area,chaotic,mass of eyes,mouths,no human features,smaller forms,cherubs,demons,golden wires,surround,holy light,tv static effect,golden glow,shadows,terrifying essence,overwhelming presence,nightmarish,landscape,sparse,cavernous,eerie,dynamic,motion,striking,awe-inspiring,nightmarish,nightmarish,nightmare,horrifying,bio-mechanical,body horror,amalgamation
  output:
    url: 2.png
- text: >-
    A robot holding a sign saying 'The Application did not respond' in red colors
  output:
    url: 3.png
- text: >-
    A photograph of Hughyen in his early twenties, (an inspiring artist whose art focuses on glitching images and vaporwave color gradients with unexpected conflicting compositions:0.5)
  output:
    url: 4.png
- text: >-
    Super Closeup Portrait, action shot, Profoundly dark whitish meadow, glass
    flowers, Stains, space grunge style, Jeanne d'Arc wearing White Olive green
    used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty,
    noisy, Vintage monk style, very detailed, hd
  output:
    url: ComfyUI_03045.png
- text: >-
    cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An
    Oscar winning movie for Best Cinematography a woman in a kimono standing on
    a subway train in Japan Kodak Motion Picture Film Style, shallow depth of
    field, vignette, highly detailed, high budget, bokeh, cinemascope, moody,
    epic, gorgeous, film grain, grainy
  output:
    url: 3.png
- text: >-
    in the style of artgerm, comic style,3D model, mythical seascape, negative
    space, space quixotic dreams, temporal hallucination, psychedelic, mystical,
    intricate details, very bright neon colors, (vantablack background:1.5),
    pointillism, pareidolia, melting, symbolism, very high contrast, chiaroscuro
  parameters:
    negative_prompt: >-
      bad quality, bad anatomy, worst quality, low quality, low resolutions,
      extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image
      artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image
  output:
    url: ComfyUI_03061_.png
- text: >-
    1980s anime portrait of a character glitching. His face is separated from
    his body by heavy static. His face is deformed by pain. Dream-like, analog
    horror, glitch, terrifying
  output:
    url: ComfyUI_03092_.png
- text: (("Proteus"):text_logo:1)
  output:
    url: ComfyUI_03297_.png
- text: >-
    dan seagrave, dante, Abandon All Hope, Ye Who Enter Here, hell religious art
    purgatory zdzislaw Beksinski, abyss inferno, lost, wanderer
  output:
    url: ComfyUI_03483_.png
license: gpl-3.0
---
<Gallery />
## ProteusV0.3

Proteus V0.3 has been advanced with an additional 200,000 anime-related images, further refined by a selection of 15,000 aesthetically pleasing images, enhancing its lighting effects significantly. This upgrade preserves its understanding of prompts and maintains its photorealistic and stylistic capabilities without suffering from catastrophic forgetting.

## Proteus

Proteus serves as a sophisticated enhancement over OpenDalleV1.1, leveraging its core functionalities to deliver superior outcomes. Key areas of advancement include heightened responsiveness to prompts and augmented creative capacities. To achieve this, it was fine-tuned using approximately 220,000 GPTV captioned images from copyright-free stock images (with some anime included), which were then normalized. Additionally, DPO (Direct Preference Optimization) was employed through a collection of 10,000 carefully selected high-quality, AI-generated image pairs.

In pursuit of optimal performance, numerous LORA (Low-Rank Adaptation) models are trained independently before being selectively incorporated into the principal model via dynamic application methods. These techniques involve targeting particular segments within the model while avoiding interference with other areas during the learning phase. Consequently, Proteus exhibits marked improvements in portraying intricate facial characteristics and lifelike skin textures, all while sustaining commendable proficiency across various aesthetic domains, notably surrealism, anime, and cartoon-style visualizations.


## Settings for ProteusV0.3

Use these settings for the best results with ProteusV0.3:

CFG Scale: Use a CFG scale of 8 to 7

Steps: 20 to 60 steps for more detail, 20 steps for faster results.

Sampler: DPM++ 2M SDE

Scheduler: Karras

Resolution: 1280x1280 or 1024x1024

please also consider using these keep words to improve your prompts:
best quality, HD, `~*~aesthetic~*~`. 

if you are having trouble coming up with prompts you can use this GPT I put together to help you refine the prompt. https://chat.openai.com/g/g-RziQNoydR-diffusion-master

## Use it with 🧨 diffusers
```python
import torch
from diffusers import (
    StableDiffusionXLPipeline, 
    KDPM2AncestralDiscreteScheduler,
    AutoencoderKL
)

# Load VAE component
vae = AutoencoderKL.from_pretrained(
    "madebyollin/sdxl-vae-fp16-fix", 
    torch_dtype=torch.float16
)

# Configure the pipeline
pipe = StableDiffusionXLPipeline.from_pretrained(
    "dataautogpt3/ProteusV0.2", 
    vae=vae,
    torch_dtype=torch.float16
)
pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.to('cuda')

# Define prompts and generate image
prompt = "black fluffy gorgeous dangerous cat animal creature, large orange eyes, big fluffy ears, piercing gaze, full moon, dark ambiance, best quality, extremely detailed"
negative_prompt = "nsfw, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, ugly, jpeg artifacts, deformed, noisy image"

image = pipe(
    prompt, 
    negative_prompt=negative_prompt, 
    width=1024,
    height=1024,
    guidance_scale=7,
    num_inference_steps=20
).images[0]
```

please support the work I do through donating to me on: 
https://www.buymeacoffee.com/DataVoid
or following me on
https://twitter.com/DataPlusEngine