Crestline Shreshth

Model Description

Crestline-Shreshth is a Stable Diffusion 1.5 LoRA fine-tuned for generating photorealistic real estate imagery. It produces high-quality visuals of residential and commercial properties, interiors, and architectural renders โ€” ideal for real estate marketing, virtual staging, and property visualization.

Model Architecture

  • Base Model: Stable Diffusion v1.5 (runwayml/stable-diffusion-v1-5)
  • Fine-tuning Method: LoRA (Low-Rank Adaptation) v2
  • Framework: Diffusers / Kohya-SS
  • Task: Text-to-Image Generation (Real Estate Domain)

Training Details

  • Training Tool: Kohya-SS LoRA trainer
  • Domain: Real estate photography โ€” interiors, exteriors, architectural renders
  • Version: v2 (improved over v1 with more training data and better trigger words)
  • Steps: Fine-tuned to convergence on curated real estate image dataset

Files

File Description
Crestline_Shreshth_v2.safetensors LoRA weights v2 (safetensors format)

Usage

from diffusers import StableDiffusionPipeline
import torch
from huggingface_hub import hf_hub_download

# Download LoRA weights
lora_path = hf_hub_download(repo_id='devanshty/Crestline-Shreshth', filename='Crestline_Shreshth_v2.safetensors')

# Load base pipeline
pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float16
).to("cuda")

# Load LoRA weights
pipe.load_lora_weights(lora_path)

# Generate
image = pipe("luxury modern living room, real estate photography, bright natural light, 4K").images[0]
image.save("output.png")

Download & Use

from huggingface_hub import hf_hub_download
lora_path = hf_hub_download(repo_id='devanshty/Crestline-Shreshth', filename='Crestline_Shreshth_v2.safetensors')
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