How to use from the
Use from the
Diffusers library
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("zenlm/zen-image-edit", 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]

Zen Image Edit

Instruction-following image editing model for targeted modifications and inpainting.

Derived from Qwen/Qwen-Image-Edit-2509 (Apache-2.0); repackaged by Zen.

Overview

This repository repackages Alibaba's Qwen-Image-Edit-2509 (QwenImageEditPlusPipeline, Qwen2.5-VL text encoder). No weights were trained from scratch by Zen.

Developed/repackaged by Hanzo AI and the Zoo Labs Foundation.

Quick Start

from diffusers import QwenImageEditPlusPipeline
import torch

pipe = QwenImageEditPlusPipeline.from_pretrained("zenlm/zen-image-edit", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")

Model Details

Attribute Value
Base model Qwen/Qwen-Image-Edit-2509
Pipeline QwenImageEditPlusPipeline
License Apache 2.0

License & Attribution

Apache 2.0. This is a derivative repackaging of Qwen-Image-Edit-2509 by Alibaba (Qwen team), released under the Apache License 2.0. All rights and attribution for the underlying model belong to the original authors.

NOTICE

This product includes the Qwen-Image-Edit-2509 model developed by Alibaba Cloud (Qwen team), licensed under the Apache License 2.0.

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