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:
- 1ca0e0d1e1fe2bc920e2312e6b57d2fb7c3cbb6c157bcf3e938ce0b416284706
- Size of remote file:
- 492 MB
- SHA256:
- fac4eeb33e8c568bda86ad43f9aa21ff8ee4547f3d17fa7064c2291a6d9fdb8c
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