Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use CCMat/fruins-ruins with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CCMat/fruins-ruins with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CCMat/fruins-ruins", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of fruins ruins in Paris in front of the Arc de triomphe, mdjrny-v4 style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ed0c3226f03174a9b858ad68998ce0f3946dc71ac01e0e0b26c4c4f9bee2be4f
- Size of remote file:
- 335 MB
- SHA256:
- 12647cc1cc0d775149d9a1835a47f5082fcb80448b68886204d35e2ae33d3eb4
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