Image-to-Image
Diffusers
Safetensors
MageFlowPipeline
image-editing
instruction-based-editing
diffusion
rectified-flow
mage-flow
Instructions to use microsoft/Mage-Flow-Edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use microsoft/Mage-Flow-Edit 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("microsoft/Mage-Flow-Edit", 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
| { | |
| "_class_name": "MageFlowPipeline", | |
| "_mage_flow_version": "0.1.0", | |
| "transformer": [ | |
| "mage_flow", | |
| "MageFlow" | |
| ], | |
| "vae": [ | |
| "mage_flow", | |
| "MageVAE" | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "Qwen3VLForConditionalGeneration" | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "AutoProcessor" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "_text_encoder_path": "text_encoder", | |
| "_vae_source": "vae/diffusion_pytorch_model.safetensors" | |
| } |