Instructions to use YaoJiefu/multiple-characters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YaoJiefu/multiple-characters 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("YaoJiefu/multiple-characters", 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
add tags for better discoverability & usability
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by linoyts HF Staff - opened
README.md
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- Qwen/Qwen-Image-Edit-2509
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pipeline_tag: image-to-image
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---
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This section introduces Lora from Qwen-Edit-2509, a tool for generating multiple characters. It can generate characters that fit the scene from almost any angle, and it can generate multiple characters!
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base_model:
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pipeline_tag: image-to-image
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library_name: diffusers
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tags:
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- lora
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---
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This section introduces Lora from Qwen-Edit-2509, a tool for generating multiple characters. It can generate characters that fit the scene from almost any angle, and it can generate multiple characters!
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