Cloth ControlNet
These are ControlNet for stable-diffusion-v1-5/stable-diffusion-v1-5. You can find some example images in the following.
Model source
- Kind
- ControlNet
- File size
- 1.35 GB
- Base model
- stable-diffusion-v1-5/stable-diffusion-v1-5
- Version
- vdiffusion_pytorch_model
- Updated
- Oct 23, 2026
- Downloads
- 4
- Source
- Hugging Face
Source description
ControlNet for cloth- Docty/cloth_controlnet
These are ControlNet for stable-diffusion-v1-5/stable-diffusion-v1-5. You can find some example images in the following.
img_0 img_1 img_2
from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler
from diffusers.utils import load_image
import torch
base_model_path = "stable-diffusion-v1-5/stable-diffusion-v1-5"
controlnet_path = "Docty/cloth_controlnet"
controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)
pipe = StableDiffusionControlNetPipeline.from_pretrained(
base_model_path, controlnet=controlnet, torch_dtype=torch.float16
)
# speed up diffusion process with faster scheduler and memory optimization
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
# remove following line if xformers is not installed or when using Torch 2.0.
#pipe.enable_xformers_memory_efficient_attention()
# memory optimization.
pipe.enable_model_cpu_offload()
control_image = load_image("./cond1.jpg")
prompt = "a professional studio photograph of an attractive model wearing a teal top with lace detail"
# generate image
#generator = torch.manual_seed(0)
image = pipe(
prompt, num_inference_steps=20, image=control_image
).images[0]
image
Sources
1 source
Sources
1 sourceVerified Oct 23
Model artifacts
1 artifact
Model artifacts
1 artifactcheckpoint-1500/controlnet/diffusion_pytorch_model.safetensors
safetensors · 1.35 GB · SHA-256 b4e20d30b864…4562 · Hugging Face
Download fileSource excerpts
3 excerpts
Source excerpts
3 excerpts--- base_model: stable-diffusion-v1-5/stable-diffusion-v1-5 inference: true license: mit library_name: diffusers instance_prompt: a professional studio photograph of an attractive model wearing a teal top with lace detail tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - controlnet - diffusers-training --- <!-- This model card has been generated automatically according to the information the training script had access to. You should probably proofread and complete it, then remove this comment. --> # ControlNet for cloth- Docty/cloth_controlnet These are ControlNet for stable-diffusion-v1-5/stable-diffusion-v1-5. You can find some example images in the following.    ```python from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCMultistepScheduler from diffusers.utils import load_image import torch base_model_path = "stable-diffusion-v1-5/stable-diffusion-v1-5" controlnet_path = "Docty/cloth_controlnet" controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16) pipe = StableDiffusionControlNetPipeline.from_pretrained( base_model_path, controlnet=controlnet, torch_dtype=torch.float16 ) # speed up diffusion process with faster scheduler and memory optimization pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config) # remove following line if xformers is not installed or when using Torch 2.0. #pipe.enable_xformers_memory_efficient_attention() # memory optimization. pipe.enable_model_cpu_offload() control_image = load_image("./cond1.jpg") prompt = "a professional studio photograph of an attractive model wearing a teal top with lace detail" # generate image #generator = torch.manual_seed(0) image = pipe( prompt, num_inference_steps=20, image=control_image ).images[0] image ```
Source context: 4 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo Docty/cloth_controlnet
Source context: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo Docty/cloth_controlnet
