Instructions to use victan/vicode_model_refiner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use victan/vicode_model_refiner with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("victan/vicode_model_refiner", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download 01.png from victan/vicode_model_refiner: direct link, hf CLI and curl.
- Browser
- Download file 5.35 MB
-
https://huggingface.co/victan/vicode_model_refiner/resolve/main/01.png
- Command line
-
hf download hf://victan/vicode_model_refiner/01.png
-
curl -L -o 01.png https://huggingface.co/victan/vicode_model_refiner/resolve/main/01.png
5.35 MB

- Xet hash:
- 59b1c9afd1fc926de2078fe022c1811bae9acfb08f29e9d6f0c6e8b4390f0bb2
- Size of remote file:
- 5.35 MB
- SHA256:
- 8fe56c6b7fffb7244dced398592b11443043d04431ab1907dc89cba5eb7fe72a
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