Instructions to use WALIDALI/samychly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/samychly with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WALIDALI/samychly", 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:
- f176605daa6332951fb2db472488ff7fdc9c3ed9e4fc06d78efd4377d4242924
- Size of remote file:
- 246 MB
- SHA256:
- 4b5aac0b2b7e9ad175e7ccc682a72b42ccc506446f14261b631832fcb597c62b
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