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HunyuanDiT v1.1 ControlNet Diffusers Depth

tencent-hunyuan-community

Fuentehuggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth/tree/1503ce418a28e5a95987a6ff357e9bd0afd8c2a5
TipoControlNetVersióndiffusion_pytorch_modelCcalidad

Fuente del modelo

Tipo
ControlNet
Tamaño del archivo
2,83 GB
Versión
vdiffusion_pytorch_model
Actualizado
6 oct 2026
Descargas
44
Fuente
Hugging Face

Descripción de la fuente

from diffusers import HunyuanDiT2DControlNetModel, HunyuanDiTControlNetPipeline
import torch
controlnet = HunyuanDiT2DControlNetModel.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth", torch_dtype=torch.float16)

pipe = HunyuanDiTControlNetPipeline.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers", controlnet=controlnet, torch_dtype=torch.float16)
pipe.to("cuda")

from diffusers.utils import load_image
cond_image = load_image('https://huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth/resolve/main/depth.jpg?download=true')

## You may also use English prompt as HunyuanDiT supports both English and Chinese
prompt = "在茂密的森林中,一只黑白相间的熊猫静静地坐在绿树红花中,周围是山川和海洋。背景是白天的森林,光线充足"
# prompt = "In the dense forest, a black and white panda sits quietly in green trees and red flowers, surrounded by mountains, rivers, and the ocean. The background is the forest in a bright environment."
image = pipe(
    prompt,
    height=1024,
    width=1024,
    control_image=cond_image,
    num_inference_steps=50,
).images[0]

Fuentes

1 fuente
Hugging FacePrincipalVersión 1503ce418a28e5a95987a6ff357e9bd0afd8c2a5
huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth/tree/1503ce418a28e5a95987a6ff357e9bd0afd8c2a5

Verificado 6 oct

Artefactos del modelo

1 artefacto

diffusion_pytorch_model.safetensors

safetensors · 2,83 GB · SHA-256 b07db85198c8…80d8 · Hugging Face

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Extractos de fuentes

3 extractos
Readme29 julhuggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth

--- license: other license_name: tencent-hunyuan-community license_link: https://huggingface.co/Tencent-Hunyuan/HunyuanDiT/blob/main/LICENSE.txt --- ```py from diffusers import HunyuanDiT2DControlNetModel, HunyuanDiTControlNetPipeline import torch controlnet = HunyuanDiT2DControlNetModel.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth", torch_dtype=torch.float16) pipe = HunyuanDiTControlNetPipeline.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.1-Diffusers", controlnet=controlnet, torch_dtype=torch.float16) pipe.to("cuda") from diffusers.utils import load_image cond_image = load_image('https://huggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth/resolve/main/depth.jpg?download=true') ## You may also use English prompt as HunyuanDiT supports both English and Chinese prompt = "在茂密的森林中，一只黑白相间的熊猫静静地坐在绿树红花中，周围是山川和海洋。背景是白天的森林，光线充足" # prompt = "In the dense forest, a black and white panda sits quietly in green trees and red flowers, surrounded by mountains, rivers, and the ocean. The background is the forest in a bright environment." image = pipe( prompt, height=1024, width=1024, control_image=cond_image, num_inference_steps=50, ).images[0] ```

Note6 octhuggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth

Source context: 44 downloads · 1 likes · Library diffusers · Repo Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth

Note29 julhuggingface.co/Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth

Source context: 5 downloads · 1 likes · Library diffusers · Repo Tencent-Hunyuan/HunyuanDiT-v1.1-ControlNet-Diffusers-Depth