README.md

---
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
  output:
    url: assets/final_output_00875_.png
- 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
  output:
    url: assets/final_output_00886_.png
- 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
  output:
    url: assets/final_output_00871_.png
- 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.
  output:
    url: assets/final_output_00895_.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: assets/final_output_00902_.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: assets/final_output_00906_.png
- text: >-
    1980s anime portrait of a character 
  output:
    url: assets/final_output_00916_.png
- text: (("Proteus"):text_logo:1)
  output:
    url: assets/final_output_00923_.png
license: apache-2.0
---
<Gallery />

# ProteusV0.5
ProteusV0.5 is the latest full release of my AI image generation model, built as a sophisticated enhancement over OpenDalleV1.1. This version brings significant improvements in photorealism, prompt comprehension, and stylistic capabilities across various domains.
About Proteus
Proteus leverages and enhances the core functionalities of OpenDalleV1.1 to deliver superior outcomes. Key areas of advancement include heightened responsiveness to prompts and augmented creative capacities. The model has been fine-tuned using a carefully curated dataset of copyright-free stock images and high-quality AI-generated image pairs.

# Key Improvements in V0.5:


Advanced Custom CLIP Integration:

- Incorporates a meticulously trained custom CLIP model
- Steadily developed over an extended period
- Further fine-tuned for specific qualities in Proteus and Prometheus
- Estimated to contribute 90% of the model's performance improvements
- Requires a clip skip setting of 2 for optimal performance

- Estimated to be responsible for 90% of the improvements in this version

Further Refinement of Stylistic Capabilities:

- Enhanced ability to generate diverse artistic styles

- Improved coherence in complex scenes and compositions

Expanded Training Dataset:

- Now totaling over 400,000 images

- Significantly broadened knowledge base and generation capabilities

Balanced Creativity and Accuracy:

- Addressed previous issues of being "too stylistic/creative"

- Improved alignment between user prompts and generated outputs

# Proteus's Background

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.

# Training Details

Total training dataset: Now over 400,000 images
Initial training: ~220,000 GPTV captioned images from copyright-free stock images (including some anime)
Additional training: Hand-picked photorealistic images
Fine-tuning: Direct Preference Optimization (DPO) with 10,000 carefully selected high-quality, AI-generated image pairs
LORA (Low-Rank Adaptation) models trained independently and selectively incorporated

# Improvements

Enhanced portrayal of intricate facial characteristics and lifelike skin textures
Improved proficiency in surrealism, anime, and cartoon-style visualizations
Superior prompt comprehension due to custom-trained CLIP
Expanded dataset leading to more diverse and accurate outputs
Refined balance between creativity and accuracy

# Recommended Settings

Clip Skip: 2
CFG Scale: 7
Steps: 25 - 50
Sampler: DPM++ 2M SDE
Scheduler: Karras
Resolution: 1024x1024

The custom-trained CLIP is a significant point of differentiation, as very few models incorporate this feature. Enjoy creating with the fully released ProteusV0.5!


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/ProteusV0.5", 
    vae=vae,
    torch_dtype=torch.float16
)
pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.to('cuda')

# Define prompts and generate image
prompt = "a cat wearing sunglasses on the beach"
negative_prompt = ""

image = pipe(
    prompt, 
    negative_prompt=negative_prompt, 
    width=1024,
    height=1024,
    guidance_scale=7,
    num_inference_steps=50,
    clip_skip=2
).images[0]


image.save("generated_image.png")
```