Instructions to use callgg/image-edit-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use callgg/image-edit-decoder 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("callgg/image-edit-decoder", 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 vae/diffusion_pytorch_model.safetensors from callgg/image-edit-decoder: direct link, hf CLI and curl.
- Browser
- Download file 254 MB
-
https://huggingface.co/callgg/image-edit-decoder/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://callgg/image-edit-decoder/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/callgg/image-edit-decoder/resolve/main/vae/diffusion_pytorch_model.safetensors
254 MB
- Xet hash:
- 2f72ef35d72eed540c565009cccc4529fcec2a0027ef8e7121653c770c8c316b
- Size of remote file:
- 254 MB
- SHA256:
- 0c8bc8b758c649abef9ea407b95408389a3b2f610d0d10fcb054fe171d0a8344
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