Instructions to use JosephusCheung/ACertainModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JosephusCheung/ACertainModel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JosephusCheung/ACertainModel", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 1b4d482be45d2f27a4170e8382e1b3620ccc23efa831cf1e96b4f07e2e20a9a6
- Size of remote file:
- 2.23 MB
- SHA256:
- a504499f5a384e7e81f5abc30cd33163d3d647f5599eaae40ce140dd4850b76c
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