Instructions to use hunyuanvideo-community/HunyuanImage-2.1-Refiner-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hunyuanvideo-community/HunyuanImage-2.1-Refiner-Diffusers 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("hunyuanvideo-community/HunyuanImage-2.1-Refiner-Diffusers", 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
Create README.md
Browse files
README.md
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```py
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from diffusers import HunyuanImageRefinerPipeline
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import torch
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from diffusers.utils import load_image
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device = "cuda:1"
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dtype = torch.bfloat16
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repo = "YiYiXu/HunyuanImage-2.1-Refiner-Diffusers"
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pipe = HunyuanImageRefinerPipeline.from_pretrained(repo, torch_dtype=dtype)
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pipe = pipe.to(device)
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prompt = "A cute, cartoon-style anthropomorphic penguin plush toy with fluffy fur, standing in a painting studio, wearing a red knitted scarf and a red beret with the word “Tencent” on it, holding a paintbrush with a focused expression as it paints an oil painting of the Mona Lisa, rendered in a photorealistic photographic style."
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image = load_image("/raid/yiyi/HunyuanImage-2.1/generated_image.png")
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generator = torch.Generator(device=device).manual_seed(649151)
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out = pipe(
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prompt,
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image=image,
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num_inference_steps=4,
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guidance_scale =3.5,
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height=2048,
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width=2048,
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generator=generator,
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).images[0]
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out.save("test_hyimage_refiner_output.png")
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```
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