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
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license: creativeml-openrail-m
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license: creativeml-openrail-m
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datasets:
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- p1atdev/pvc
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language:
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- en
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tags:
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- stable-diffusion
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- text-to-image
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- diffusers
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- safetensors
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# PVC
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