Instructions to use Hayoo8/test-pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Hayoo8/test-pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Hayoo8/test-pipeline", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- b018ab40702004cf3cd928c37aedfe1938847492fb89872dbb8dccdf2265e454
- Size of remote file:
- 2.65 MB
- SHA256:
- 2a6565692b5eaade929997969e8416b62c2e2829a3bf2dc28218c255d3a9584f
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