Instructions to use fancyfeast/bigasp-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fancyfeast/bigasp-v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fancyfeast/bigasp-v1", 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:
- b8d9b752bc8584e6f7f1700e9dfa989702280b896d6a9a04fab9bc97dce443d3
- Size of remote file:
- 492 MB
- SHA256:
- 55fd0fcaeab68258828ba8e6f2b57615ed737309b6525255e1c7c8caf2f0ca70
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