simonschoe/iridescent-jellyfish

Iridescent Jellyfish

Iridescent Jellyfish is a Dreambooth model for the iridescent jellyfish concept (represented by the ðŁĴŁ identifier). It applies to the animal theme. It is fine-tuned from runwayml/stable-diffusion-v1-5 checkpoint on a small dataset of jellyfish images. It can be used by modifying the instance_prompt: a photo of a ðŁĴŁ jellyfish in the snow

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: 17
• Learning rate: 2e-06
• Training steps: 800
• Guidance Scale: 7
• Inference Steps: 50

Output Examples

a oil painting of a ðŁĴŁ jellyfish	a photo of a ðŁĴŁ jellyfish next to a dog	a photo of a ðŁĴŁ jellyfish in the snow
a photo of a ðŁĴŁ jellyfish on top of a mountain	a photo of a ðŁĴŁ jellyfish in the sky	a photo of a ðŁĴŁ jellyfish
a photo of a ðŁĴŁ jellyfish skydiving	a photo of a ðŁĴŁ jellyfish sutfing on a surfboard	a photo of a choclate ðŁĴŁ jellyfish
a photo of a ðŁĴŁ jellyfish shooting fireworks in the sky	a photo of a ðŁĴŁ jellyfish on rollerblades	a photo of a ðŁĴŁ jellyfish in a beer bottle
a colorful sketch of a ðŁĴŁ jellyfish	a photo of a ðŁĴŁ jellyfish in the jungle	a mystic ðŁĴŁ jellyfish, trending on artstation

Usage

from diffusers import StableDiffusionPipeline
import torch

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

prompt = "a photo of a ðŁĴŁ jellyfish in the snow"

image = pipeline(
    prompt,
    num_inference_steps=50,
    guidance_scale=7,
    num_images_per_prompt=1
).images[0]

image