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:
- 32c4ab4f2fce5e096554386cb9fa5abe5a6e4bac3ab7d58fc9c1020c20cbf80d
- Size of remote file:
- 3.44 GB
- SHA256:
- 7f18c4fa7f5c8228a9926ce7800177751206db30eb890eb69c7f7a4053a0828f
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