Instructions to use WALIDALI/imentunisly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WALIDALI/imentunisly 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/imentunisly", 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:
- 28566507b0d493512035d09a61e1b1e2bb309224aafa3c4cba9fec68ffc53b7e
- Size of remote file:
- 246 MB
- SHA256:
- b3be260c87d813420ca485c16efc510b0ce1ccf722b0f4e934a7235e82e3654e
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