Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
science
Instructions to use dreambooth-hackathon/glxy-galaxy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dreambooth-hackathon/glxy-galaxy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dreambooth-hackathon/glxy-galaxy", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of glxy galaxy" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth model for glxy trained by lewtun on the lewtun/galaxies dataset.
This your the Stable Diffusion model fine-tuned the glxy concept taught to Stable Diffusion with DreamBooth.
It can be used by modifying the instance_prompt: a photo of glxy galaxy
This model was created as part of the DreamBooth Hackathon. Visit the organisation page for instructions on how to take part!
Description
Describe your model and concept here.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('dreambooth-hackathon/glxy-galaxy')
image = pipeline().images[0]
image
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