Image-to-Image
Diffusers
Safetensors
English
orbitquant
w4a8
4-bit precision
gptq
quantized
fibo
vgl
structured-prompts
image-editing
arxiv:2607.02461
Instructions to use WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8 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("WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8", 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 assets/edits_original_vs_orbitquant_w4a8.webp from WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8: direct link, hf CLI and curl.
- Browser
- Download file 812 kB
-
https://huggingface.co/WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8/resolve/main/assets/edits_original_vs_orbitquant_w4a8.webp
- Command line
-
hf download hf://WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8/assets/edits_original_vs_orbitquant_w4a8.webp
-
curl -L -o edits_original_vs_orbitquant_w4a8.webp https://huggingface.co/WaveCut/Fibo-2.0-edit-turbo-OrbitQuant-W4A8/resolve/main/assets/edits_original_vs_orbitquant_w4a8.webp
812 kB

- Xet hash:
- 48ae0393829c19507e1b5f4def97c77dd5bc20e13bb801a5d7b8274af8b034b0
- Size of remote file:
- 812 kB
- SHA256:
- fd67d60f8171af12eade6b4ca4637cf918f02e8fbcd4b77569e05a9f1a0eb98e
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