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:
- 106148e9c715382983ac82d4621553b37cdc7b3759d616b0e3f51263f69bdb66
- Size of remote file:
- 1.36 GB
- SHA256:
- 4c6fa00e2e8809ce1f2a0efe55d49242e9e14402a73ee9bc566d8486ac4650ae
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