Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("harveymannering/jurassic-coast", dtype=torch.bfloat16, device_map="cuda")
prompt = "a photo of ioprt cliff with a dog"
image = pipe(prompt).images[0]DreamBooth Hackathon model for the Isle of Portland concept trained by harveymannering on the jurassic-coast dataset.
The model was fine-tuned on the cliff prior for the landscape theme. I used the jurassic-coast dataset which contains 14 images of a particular cliff on the Isle of Portland on the south coast of England.
This is a Stable Diffusion model fine-tuned on the Isle of Portland (shortened to the rare token ioprt) concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of ioprt cliff
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
Examples
| In the style of different artists
"a photo of ioprt cliff in the style of monet" |
"a photo of ioprt cliff in the style of raphael" |
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| Adding things to the environment "a photo of ioprt cliff with a dog" |
"a photo of ioprt cliff with a boat" |
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| Making changes to the environment "a photo of a sunset at ioprt cliff" |
"a photo of ioprt cliff in the desert" |
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Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('harveymannering/jurassic-coast')
image = pipeline().images[0]
image
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