Instructions to use rain1011/pyramid-flow-sd3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rain1011/pyramid-flow-sd3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("rain1011/pyramid-flow-sd3", torch_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:
- 807015ece284a4a232f2e7b0390cd0409647558fb74209ba5999d18e6459bcc8
- Size of remote file:
- 8.34 GB
- SHA256:
- 7262ac5271e549ea87b8b05610663f16cf490eec19f525d4e2709c929cf52665
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.