Text-to-Image
Diffusers
PyTorch
StableDiffusionPipeline
stable-diffusion
diffusion-models-class
dreambooth-hackathon
landscape
Instructions to use nahidalam/landscape-ocean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nahidalam/landscape-ocean with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nahidalam/landscape-ocean", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of landscape ocean in the Acropolis" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 9590cab35c65f30c1c1266138730ac074dbbc5641bc6cf584c9b13494f71a6cb
- Size of remote file:
- 3.44 GB
- SHA256:
- 69795360f05b524056df6876a4fddea329219f18555270bb099f7744fa39924b
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