Instructions to use james16/PropFly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use james16/PropFly with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("james16/PropFly", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39d52b42f1ddf0f47f89391455b6c400a4a083330394bd7cf50654b7a05b36ec
- Size of remote file:
- 4.73 GB
- SHA256:
- b09d68ea69194f5874f4cf87edb8e06974f9d7939777ec4d7db34b8c0e8f481c
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