Instructions to use vdo/potat1-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vdo/potat1-5000 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/potat1-5000", 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:
- 76f785fc9562e6ce4893640a7f51ee977b7dec9ad382135cbb70188abe50e953
- Size of remote file:
- 681 MB
- SHA256:
- 411ce9fe97aa796fe26d3f2c61a19a26b0261c5e139b7796bdc5d6c5491ca05b
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