Instructions to use vdo/pyramid-flow-sd3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vdo/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("vdo/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 causal_video_vae/diffusion_pytorch_model.bin from vdo/pyramid-flow-sd3: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/vdo/pyramid-flow-sd3/resolve/main/causal_video_vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://vdo/pyramid-flow-sd3/causal_video_vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/vdo/pyramid-flow-sd3/resolve/main/causal_video_vae/diffusion_pytorch_model.bin
1.34 GB
- Xet hash:
- 459579a8a6fec60730a1a8ad4332713d52405831509110829a0bce394704eff2
- Size of remote file:
- 1.34 GB
- SHA256:
- 8385177ef6dc62f9e0665213c1509f750a59b496ddf573b4524d7a641b21d260
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