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The Pokeball Machine

The Pokeball Machine is a Dreambooth model for the pokeball concept (represented by the pkblz identifier). It applies to the wildcard theme. It is fine-tuned from CompVis/stable-diffusion-v1-4 checkpoint on a small dataset of pokeball images (i.e., images of the red-white original pokeball). It can be used by modifying the instance_prompt: a pkblz ball in the middle of a miniature jungle

This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!

Fine-Tuning Details

  • Number of training images: 31
  • Learning rate: 2e-06
  • Training steps: 800
  • Guidance Scale: 10
  • Inference Steps: 50-75

Output Examples

a blueprint photo of a pkblz ball a photo of a cybernetic pkblz ball, wide shot a photo of a pkblz ball in the style vintage disney
a photo of a mosaic pkblz ball lying in an antique temple a photo of a detailed ornate pkblz ball a pkblz ball underwater
a pkblz ball in the middle of a miniature jungle a pkblz ball underwater a mystic pkblz ball, trending on artstation
a pkblz ball underwater, trending on artstation a wooden pkblz ball a pkblz ball hovering over a pond
a pkblz ball on a sunny tropical beach a steampunk pkblz ball, trending on artstation a colored pencil sketch of a pkblz ball
a photo of a spectral ornate pkblz ball, trending on artstation, realistic a sunset photo of a pkblz ball a watercolor photo of a pkblz ball

Usage

from diffusers import StableDiffusionPipeline
import torch

device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
pipeline = StableDiffusionPipeline.from_pretrained('simonschoe/pokeball-machine').to(device)

prompt = "a pkblz ball in the middle of a miniature jungle"

image = pipeline(
    prompt,
    num_inference_steps=50,
    guidance_scale=10,
    num_images_per_prompt=1
).images[0]

image
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