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
Commit History
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Add pipeline tag and library name, and update content
Verified signatureThis PR ensures people can find your model at https://huggingface.co/models?pipeline_tag=text-to-video. It also makes sure the "how to use" button appears, indicating the model is compatible with the Diffusers library. The content of the model card is updated to reflect the current state of the model, incorporating information from the GitHub README.1f03464
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thanks to rain1011 ❤
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initial commit
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