metadata
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- animal
widget:
- text: a photo of a ðŁĴŁ jellyfish in the snow
- text: a photo of a ðŁĴŁ jellyfish next to a dog
- text: a photo of a ðŁĴŁ jellyfish on top of a mountain
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 colorful sketch of a ðŁĴŁ jellyfish | a photo of a ðŁĴŁ jellyfish in the jungle | a mystic ðŁĴŁ jellyfish, trending on artstation |
.png) |
.png) |
.png) |
| 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 |
.png) |
.png) |
.png) |
| 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 |
.png) |
.png) |
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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