Instructions to use lavinal712/NextStep-1-f8ch16-Tokenizer-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lavinal712/NextStep-1-f8ch16-Tokenizer-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lavinal712/NextStep-1-f8ch16-Tokenizer-diffusers", 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:
- 8062f42c4c1a3c17b191d7932093bdc5e2d8a0e83f77fb5587ecddea26c6ad98
- Size of remote file:
- 335 MB
- SHA256:
- d67ef6afe4ec377d53e99b270cf9a5f346f4c21dfe00732e2043b5b4c42ba394
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