Instructions to use Ziyaad30/Pyramid-Flow-sd3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ziyaad30/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("Ziyaad30/Pyramid-Flow-sd3", 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
Download diffusion_transformer_384p/diffusion_pytorch_model.bin from Ziyaad30/Pyramid-Flow-sd3: direct link, hf CLI and curl.
- Browser
- Download file 8.34 GB
-
https://huggingface.co/Ziyaad30/Pyramid-Flow-sd3/resolve/main/diffusion_transformer_384p/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Ziyaad30/Pyramid-Flow-sd3/diffusion_transformer_384p/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Ziyaad30/Pyramid-Flow-sd3/resolve/main/diffusion_transformer_384p/diffusion_pytorch_model.bin
8.34 GB
- Xet hash:
- cf146619a3ef863826c17166475b7a00e976cd26d455f6557e9649f8eab70349
- Size of remote file:
- 8.34 GB
- SHA256:
- d73e70c1fa5c19ac4d76116b2ced39d56ae22b40c84999075f8f668e22eb91f9
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