metadata
license: c-uda
datasets:
- SadilKhan/CADCap-1M
language:
- en
base_model:
- stabilityai/stable-diffusion-3.5-medium
tags:
- text-to-image
- cad
- dreamcad
- fine-tuned
Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces
Overview
This repo contains the fine-tuned Stable Diffusion 3.5 used as the text-to-image component of DreamCAD — a multi-modal generative framework for scalable CAD generation via differentiable parametric surfaces.
DreamCAD adopts a two-stage approach to text-to-CAD generation:
Text Prompt ──► [This model] SD 3.5 (fine-tuned) ──► CAD-style image ──► Image-to-CAD model ──► STEP file
💡 Direct text-to-CAD generation is notoriously difficult without visual grounding. This model bridges that gap by generating CAD-style images that provide the geometric and structural grounding needed for downstream image-to-CAD reconstruction.
Usage
Install dependencies
pip install diffusers transformers accelerate
For Text-to-Image Generation (CAD-style)
from diffusers import StableDiffusion3Pipeline
import torch
DEFAULT_TEXT ="A CAD model of "
HF_TOKEN = "YOUR_TOKEN_ID"
os.environ["HF_TOKEN"] = HF_TOKEN
# Load the base model first
pipe = StableDiffusion3Pipeline.from_pretrained(
"stabilityai/stable-diffusion-3.5-medium",
torch_dtype=torch.float16,
cache_dir="/netscratch/mokhan/.cache",
)
# Load and fuse the DreamCAD LoRA
pipe.load_lora_weights(
"SadilKhan/DreamCAD",
weight_name="dreamcad_sd35/pytorch_lora_weights.safetensors",
token=HF_TOKEN,
)
pipe = pipe.to("cuda")
image = pipe(DEFAULT_TEXT + "Ergonomic office chair with curved backrest frame, adjustable armrests, and five-spoke base with casters.").images[0]
image.save("output.png")
Citation
If you find DreamCAD useful, please cite
@article{khan2026dreamcad,
title={DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces},
author={Khan, Mohammad Sadil and Usama, Muhammad and Potamias, Rolandos Alexandros and Stricker, Didier and Afzal, Muhammad Zeshan and Deng, Jiankang and Elezi, Ismail},
journal={arXiv preprint arXiv:2603.05607},
year={2026}
}
License
This model inherits the Stability AI Community License from the base model.
- ✅ Free for research and non-commercial use
- ✅ Free for commercial use if your org has < $1M annual revenue
- ❌ Requires an Enterprise License above $1M revenue