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--- |
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license: mit |
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tags: |
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- molecular-generation |
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- controlnet |
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- chemistry |
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- scent-to-molecule |
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- text-to-smiles |
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- pytorch |
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library_name: pytorch |
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pipeline_tag: text-generation |
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base_model: molecular-diffusion |
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language: |
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- en |
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datasets: |
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- sensory-molecules |
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metrics: |
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- mse |
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- bce |
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model-index: |
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- name: scent-to-molecule-controlnet |
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results: |
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- task: |
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type: text-to-molecular-generation |
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name: Text to Molecular Generation |
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dataset: |
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type: sensory-molecules |
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name: Sensory Molecules Dataset |
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metrics: |
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- type: validation_loss |
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value: 0.030441686697304248 |
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name: Validation Loss |
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--- |
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# 🧬 Scent to Molecule Controt |
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A ControlNet-style model that generates molecular structures (SMILES) from scent descriptions. |
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## Model Description |
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This model converts natural language scent descriptions into chemically valid SMILES representations of molecules that would produce those scents. |
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## Model Details |
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- **Training epochs**: 20 |
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- **Best validation loss**: 0.030441686697304248 |
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- **Model size**: 2.9 MB |
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- **Architecture**: ControlNet-style adapter with frozen molecular backbone |
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- **Text encoder**: sentence-transformers/all-MiniLM-L6-v2 |
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## Usage |
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```python |
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from huggingface_hub import hf_hub_download |
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import torch |
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# Download model |
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model_path = hf_hub_download("munchers/scent-to-molecule", "best_control.pt") |
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checkpoint = torch.load(model_path, map_location='cpu') |
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``` |
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## Examples |
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| Input Description | Expected Output | Chemical Type | |
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|------------------|-----------------|---------------| |
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| "sweet vanilla scent" | Vanillin-like compounds | Phenolic aldehyde | |
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| "bitter coffee alkaloid" | Caffeine-like compounds | Purine alkaloid | |
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| "minty cooling fresh" | Menthol-like compounds | Monoterpene alcohol | |
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## Training Data |
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- **Training samples**: 815 compounds |
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- **Validation samples**: 157 compounds |
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- **Chemical categories**: 8 (esters, aldehydes, terpenes, phenolics, etc.) |
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## Limitations |
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- Uses mock molecular backbone (not full physics simulation) |
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- Template-based SMILES generation |
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- English-only descriptions |
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- Synthetic training dataset |
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## Citation |
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```bibtex |
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@misc{scent-to-molecule-controlnet, |
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title={Scent-to-Molecule Control}, |
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author={Shiva Mudide}, |
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year={2025}, |
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howpublished={\url{https://huggingface.co/munchers/scent-to-molecule}} |
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} |
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``` |
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