Image-to-Image
Diffusers
Safetensors
MageFlowPipeline
image-editing
instruction-based-editing
diffusion
rectified-flow
mage-flow
Instructions to use natalie5/Mage-Flow-Edit-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use natalie5/Mage-Flow-Edit-Base 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("natalie5/Mage-Flow-Edit-Base", 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/dog.jpg from natalie5/Mage-Flow-Edit-Base: direct link, hf CLI and curl.
- Browser
- Download file 525 kB
-
https://huggingface.co/natalie5/Mage-Flow-Edit-Base/resolve/main/assets/dog.jpg
- Command line
-
hf download hf://natalie5/Mage-Flow-Edit-Base/assets/dog.jpg
-
curl -L -o dog.jpg https://huggingface.co/natalie5/Mage-Flow-Edit-Base/resolve/main/assets/dog.jpg
525 kB

- Xet hash:
- 08bfd0989a332703031c26fa370b188c14cdf92db5ed1230393c7a6347e9ca98
- Size of remote file:
- 525 kB
- SHA256:
- 164d8dfe707fb854e288ad2eea65c2db87e90af11f689c85502860eeaf3f4794
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