Instructions to use dx8152/Qwen-Image-Edit-2511-Gaussian-Splash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dx8152/Qwen-Image-Edit-2511-Gaussian-Splash 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-2511", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2511-Gaussian-Splash") 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
- Local Apps Settings
- Draw Things
add library tag for better usability & analytics (#4)
Browse files- add library tag for better usability & analytics (74d6b159b96c1b2d9ba8fd18e6997f1f77a01138)
Co-authored-by: Linoy Tsaban <linoyts@users.noreply.huggingface.co>
README.md
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pipeline_tag: image-to-image
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tags:
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- lora
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---
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This model is trained (code-free!) on ModelScope. Thanks to ModelScope team for providing the training infra:
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The prompt message is the default: "高斯泼溅,参考图2的场景图,修复图1的场景图透视并修复空白区域"
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pipeline_tag: image-to-image
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tags:
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- lora
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library_name: diffusers
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---
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This model is trained (code-free!) on ModelScope. Thanks to ModelScope team for providing the training infra:
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The prompt message is the default: "高斯泼溅,参考图2的场景图,修复图1的场景图透视并修复空白区域"
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