Image-to-Image
Diffusers
Safetensors
MageFlowPipeline
image-editing
instruction-based-editing
diffusion
rectified-flow
mage-flow
Instructions to use SceneWorks/Mage-Flow-Edit-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SceneWorks/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("SceneWorks/Mage-Flow-Edit-Base", torch_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:
- 5f6e5eaaec3e393d1a01c61ec0ef7ad388a5d3582661620e9eb2711c5d526787
- Size of remote file:
- 8.23 GB
- SHA256:
- 9d93faa75963ba4a2ef1b64bed4fe94c2554b82e8f3fb2dbb267604a634d450d
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