from huggingface_hub import hf_hub_download
import torch

# Download model
model_path = hf_hub_download("munchers/scent-to-molecule", "best_control.pt")

model.load_state_dict(checkpoint['model_state_dict'])
if torch.cuda.is_available():
    model = model.cuda()

Examples

Input Description	Expected Output	Chemical Type
"sweet vanilla scent"	Vanillin-like compounds	Phenolic aldehyde
"bitter coffee alkaloid"	Caffeine-like compounds	Purine alkaloid
"minty cooling fresh"	Menthol-like compounds	Monoterpene alcohol

Training Data

Training samples: 815 compounds
Validation samples: 157 compounds
Chemical categories: 8 (esters, aldehydes, terpenes, phenolics, etc.)

Limitations

Uses mock molecular backbone (not full physics simulation)
Template-based SMILES generation
English-only descriptions
Synthetic training dataset

Citation

bibtex

@misc{scent-to-molecule-controlnet,
  title={Scent-to-Molecule Control},
  author={Shiva Mudide},
  year={2025},
  howpublished={\url{https://huggingface.co/munchers/scent-to-molecule}}
}