Instructions to use Siyam/testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Siyam/testing with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Siyam/testing", 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:
- 9e3f07d267701e26ad059e55eaa7f105aaaf8becebe9ff1e938b343ccb02ab0e
- Size of remote file:
- 492 MB
- SHA256:
- a3746c304841beae2f746494c1ca981fa485c56661b1888e2d38276e8ea16dd6
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