Text-to-Image
Diffusers
Safetensors
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
wildcard
Instructions to use Stepa/cyberPUUNK-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Stepa/cyberPUUNK-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Stepa/cyberPUUNK-style", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of cyberPUUNK style in the Acropolis" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DreamBooth model for the cyberPUUNK concept trained by Stepa on the SuperrWu/Cyberpunk dataset.
This is a Stable Diffusion model fine-tuned on the cyberPUUNK concept with DreamBooth. It can be used by modifying the instance_prompt: a super cool photo of cyberPUUNK style
This model was created as part of the DreamBooth Hackathon ๐ฅ. Visit the organisation page for instructions on how to take part!
Description
This is a Stable Diffusion model fine-tuned on style images for the wildcard theme.
Usage
from diffusers import StableDiffusionPipeline
pipeline = StableDiffusionPipeline.from_pretrained('Stepa/cyberPUUNK-style')
image = pipeline().images[0]
image
- Downloads last month
- 4