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
from diffusers import HunyuanImageRefinerPipeline
import torch
from diffusers.utils import load_image
device = "cuda:1"
dtype = torch.bfloat16
repo = "YiYiXu/HunyuanImage-2.1-Refiner-Diffusers"
pipe = HunyuanImageRefinerPipeline.from_pretrained(repo, torch_dtype=dtype)
pipe = pipe.to(device)
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."
image = load_image("/raid/yiyi/HunyuanImage-2.1/generated_image.png")
generator = torch.Generator(device=device).manual_seed(649151)
out = pipe(
prompt,
image=image,
num_inference_steps=4,
guidance_scale =3.5,
height=2048,
width=2048,
generator=generator,
).images[0]
out.save("test_hyimage_refiner_output.png")