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 Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from p1atdev/pvc: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/p1atdev/pvc/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://p1atdev/pvc/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/p1atdev/pvc/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- ddf20842b6f99bd579675e6110f2104d294b16abf9c64569d6d5d2533fdc33d3
- Size of remote file:
- 335 MB
- SHA256:
- d7ba0d96a27ca3a8621b034de4637211707a744265b1fec8b3c7718c42182340
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