Instructions to use hunyuanvideo-community/HunyuanImage-2.1-Distilled-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-Distilled-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hunyuanvideo-community/HunyuanImage-2.1-Distilled-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 1,098 Bytes
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license: other
license_name: tencent-hunyuan-community
license_link: https://github.com/Tencent-Hunyuan/HunyuanImage-2.1/blob/master/LICENSE
language:
- en
- zh
pipeline_tag: text-to-image
library_name: diffusers
---
```py
from diffusers import HunyuanImagePipeline
import torch
device = "cuda:0"
dtype = torch.bfloat16
repo = "hunyuanvideo-community/HunyuanImage-2.1-Distilled-Diffusers"
pipe = HunyuanImagePipeline.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."
generator = torch.Generator(device=device).manual_seed(649151)
out = pipe(
prompt,
num_inference_steps=8,
distilled_guidance_scale =3.5,
height=2048,
width=2048,
generator=generator,
).images[0]
out.save("test_hyimage-distilled_output.png")
``` |