README.md

metadata

library_name: diffusers
license: mit
tags:
  - art

Model Description

This model combines the capabilities of the stable diffusion medium model with a Civit AI text-to-image model fine-tuned on a custom dataset of high-quality images. It aims to generate realistic and detailed images based on textual prompts.

• Developed by: M.Cihan Yalçın
• Model type: Stable Diffusion
• License: MIT
• Finetuned from models:
  • stabilityai/stable-diffusion-3-medium-diffusers
  • CyberRealistic

Uses

Direct Use

from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained(
                    "Chan-Y/Cyber-Stable-Realistic", 
                    torch_dtype=torch.float16).to("cuda")

prompt = "A bowl of ramen shaped like a cute kawaii bear, by Feng Zikai"
negative = ""
image = pipeline(prompt,
                negative_prompt=negative).images[0]
image

Bias, Risks, and Limitations

• The model may not always perfectly capture highly complex or abstract concepts.
• The quality of the output can be influenced by the specificity and clarity of the prompt.
• Ethical considerations should be taken into account when generating images to avoid misuse.

Finetuning Details

Finetuning Data

• Model is finetuned with sentetic high quality images collected from high performance Text-to-Image models.