Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
animal
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("sanderland/zelda-the-cat", dtype=torch.bfloat16, device_map="cuda")
prompt = "a photo of a zzelda cat in space"
image = pipe(prompt).images[0]DreamBooth model for the zzelda concept trained by Sanderbaduk on dataset of cats.
This is a Stable Diffusion model fine-tuned on pictures of my mum's cat "Zelda" with DreamBooth. It can be used by using the phrase 'zzelda cat' in a prompt.
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
| One of the images used to fine-tune on "a photo of zzelda cat on a chair" |
One of the images generated by the model "a photo of zzelda cat in space" |
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Description
This is a Stable Diffusion model fine-tuned on images of my mum's cat Zelda for the animal theme.
To experiment a bit, I used a custom prompt for each image based on the file name. This works, but does not seem to have made much of a difference. The model was trained on CPU after encountering issues with CUDA, taking around 2 hours on 32 cores.
It works a lot better locally than in the widget, where it tends to take a few more tries to get the right cat.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Sanderbaduk/zelda-the-cat')
image = pipeline().images[0]
image
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