Instructions to use p1atdev/pvc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use p1atdev/pvc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("p1atdev/pvc", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, high quality, 1girl, cat ears, silver, blue, frills, bow, looking at viewer, ultra detailed" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 8cab82d2d76f5900141c0a5f7329ef1bb35a368bbf5a642a3bb23f7267685a03
- Size of remote file:
- 2.05 MB
- SHA256:
- 71ce203ddb8d07bc43efb2db3f1544221091f73a09d5d6f74340fd0e8c3d950c
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