Instructions to use Boogu/Boogu-Image-0.1-Edit-Turbo-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Boogu/Boogu-Image-0.1-Edit-Turbo-fp8 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("Boogu/Boogu-Image-0.1-Edit-Turbo-fp8", 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
- Xet hash:
- 520109db7762c4ca88bdfa88715c731207ae267dff45c152184a06798d7340bb
- Size of remote file:
- 13.2 MB
- SHA256:
- 06167f021df04fb260a0bd11f44503d94cac1e3d0d360584badfdb7d641e49cd
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