Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
science
Instructions to use kzipa/ferrofluid-fluid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kzipa/ferrofluid-fluid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kzipa/ferrofluid-fluid", dtype=torch.bfloat16, device_map="cuda") prompt = "ferrofluid fluid greets magnet, photorealistic, hd" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth model for the ferrofluid concept trained by kzipa on the kzipa/ferrofluid dataset.
This is a Stable Diffusion model fine-tuned on the ferrofluid concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of ferrofluid fluid
This model was created as part of the DreamBooth Hackathon 🔥. Visit the organisation page for instructions on how to take part!
Description
This is a Stable Diffusion model fine-tuned on fluid images for the science theme.
ferrofluid fluid greets magnet, photorealistic, hd
ferrofluid fluid river, oil painting
a photo of a mouse covered by ferrofluid fluid
a photo of ferrofluid fluid on a top of Christmas tree
ferrofluid fluid and a cute magnet are kissing in the sunset, romantic
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('kzipa/ferrofluid-fluid')
image = pipeline().images[0]
image
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