Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use CCMat/fgreeneruins-ruins with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CCMat/fgreeneruins-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/fgreeneruins-ruins", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "high quality photo of Venice in fgreeneruins ruins" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cc6e4078337605ea0174c53954d4a0e429d83ed852f62acd209405b116e7bbf0
- Size of remote file:
- 335 MB
- SHA256:
- 2a4501afd14c7feca6b67d5d4869c75c5db51c262c1193efebfd3227d92f50d8
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