Instructions to use Qwen/Qwen-Image-Edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Qwen/Qwen-Image-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("Qwen/Qwen-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] - Inference
- Notebooks
- Google Colab
- Kaggle
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@@ -89,7 +89,6 @@ Here’s another interesting example—removing fine strands of hair:
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Below shows how to modify the color of text in an image—changing the color of the letter "n" to blue:
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Appearance editing is also crucial in modifying human poses, backgrounds, and clothing, as demonstrated in the following three images:
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The second hallmark of Qwen-Image-Edit is its accurate text editing, made possible by Qwen-Image’s powerful text rendering capabilities.
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Below shows how to modify the color of text in an image—changing the color of the letter "n" to blue:
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Appearance editing is also crucial in modifying human poses, backgrounds, and clothing, as demonstrated in the following three images:
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The second hallmark of Qwen-Image-Edit is its accurate text editing, made possible by Qwen-Image’s powerful text rendering capabilities.
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