Text-to-Image
Diffusers
StableDiffusionPipeline
stablediffusionapi.com
stable-diffusion-api
ultra-realistic
Instructions to use Masoond/counterfeit-v30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Masoond/counterfeit-v30 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Masoond/counterfeit-v30", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from Masoond/counterfeit-v30: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/Masoond/counterfeit-v30/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Masoond/counterfeit-v30/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Masoond/counterfeit-v30/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 3bc0df59155cf14b8bbf39f9f7cbb0e213a80ca9d2800a3ffa67fabb49a7da83
- Size of remote file:
- 335 MB
- SHA256:
- 75e3c6653316ea284aa71bb38b8d8fc229061e295684006d4309b855f50f5054
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