Downloads · 30 days
14
3% of all-time downloads
reemas-irasna/home-decor_LoRA
home-decor_LoRA is a text-to-image model from reemas-irasna. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as openrail++.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
14
3% of all-time downloads
All-time downloads
511
Public
Repo size
38.4 MB
Likes
1
Public
Click a slice to open those files.
.safetensors23.4 MB · 61%
From the Hugging Face model README
Using Stable Diffusion XL 1.5, trained a custom model for image generation of Home Decor usecase Also applied Canny ControlNets to it for better performance.
Training Notebook - https://www.kaggle.com/code/reemasirasna/sdxl-training-decor
ControlNet Notebook - https://www.kaggle.com/code/reemasirasna/sdxl-controlnet-decor
Below are the generated images from this model.



These are reemas-irasna/home-decor_LoRA LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
You should use "a photo of home" to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
import torch
from diffusers import DiffusionPipeline, AutoencoderKL
vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
pipe = DiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
vae=vae,
torch_dtype=torch.float16,
variant="fp16",
use_safetensors=True
)
pipe.load_lora_weights("reemas-irasna/home-decor_LoRA")
_ = pipe.to("cuda")
prompt = "a photo of bedroom in red and white combination"
image = pipe(prompt=prompt, num_inference_steps=25).images[0]
image