pipeline_tag: text-to-image
widget:
- text: >-
black fluffy gorgeous dangerous cat animal creature, large orange eyes,
big fluffy ears, piercing gaze, full moon, dark ambiance, best quality,
extremely detailed
- text: >-
(impressionistic realism by csybgh), a 50 something male, working in
banking, very short dyed dark curly balding hair, Afro-Asiatic ancestry,
talks a lot but listens poorly, stuck in the past, wearing a suit, he has
a certain charm, bronze skintone, sitting in a bar at night, he is smoking
and feeling cool, drunk on plum wine, masterpiece, 8k, hyper detailed,
smokey ambiance, perfect hands AND fingers
- text: >-
high quality pixel art, a pixel art silhouette of an anime space-themed
girl in a space-punk steampunk style, lying in her bed by the window of a
spaceship, smoking, with a rustic feel. The image should embody epic
portraiture and double exposure, featuring an isolated landscape visible
through the window. The colors should primarily be dynamic and
action-packed, with a strong use of negative space. The entire artwork
should be in pixel art style, emphasizing the characters shape and set
against a white background. Silhouette
- text: >-
The image features an older man, a long white beard and mustache, He has
a stern expression, giving the impression of a wise and experienced
individual. The mans beard and mustache are prominent, adding to his
distinguished appearance. The close-up shot of the mans face emphasizes
his facial features and the intensity of his gaze.
- 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
- 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
- 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
- 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
- text: (("Proteus"):text_logo:1)
- text: >-
dan seagrave, dante, Abandon All Hope, Ye Who Enter Here, hell religious
art purgatory zdzislaw Beksinski, abyss inferno, lost, wanderer
license: gpl-3.0
fp16 Fork of dataautogpt3/ProteusV0.2
merged with RealCartoonXL to fix issues with inability to understand tags related to anime or cartoon styles at just a weight of 0.5% out of 100% using custom scripts with slerp like methods.
Version 0.2 shows subtle yet significant improvements over Version 0.1. It demonstrates enhanced prompt understanding that surpasses MJ6, while also approaching its stylistic capabilities.
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 ProteusV0.2
Use these settings for the best results with ProteusV0.2:
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
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