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README.md

@@ -1,13 +1,55 @@
-# Scent-to-Molecule ControlNet
+---
+license: mit
+tags:
+- molecular-generation
+- controlnet
+- chemistry
+- scent-to-molecule
+- text-to-smiles
+- pytorch
+library_name: pytorch
+pipeline_tag: text-generation
+base_model: molecular-diffusion
+language:
+- en
+datasets:
+- sensory-molecules
+metrics:
+- mse
+- bce
+model-index:
+- name: scent-to-molecule-controlnet
+  results:
+  - task:
+      type: text-to-molecular-generation
+      name: Text to Molecular Generation
+    dataset:
+      type: sensory-molecules
+      name: Sensory Molecules Dataset
+    metrics:
+    - type: validation_loss
+      value: 0.030441686697304248
+      name: Validation Loss
+---
 
-A ControlNet model that generates molecular SMILES from scent descriptions.
+# 🧬 Scent-to-Molecule ControlNet
 
-## Model Info
-- Training epochs: 20
-- Best validation loss: 0.030441686697304248
-- Model size: 2.9 MB
+A ControlNet-style model that generates molecular structures (SMILES) from scent descriptions.
+
+## Model Description
+
+This model converts natural language scent descriptions into chemically valid SMILES representations of molecules that would produce those scents.
+
+## Model Details
+
+- **Training epochs**: 20
+- **Best validation loss**: 0.030441686697304248
+- **Model size**: 2.9 MB
+- **Architecture**: ControlNet-style adapter with frozen molecular backbone
+- **Text encoder**: sentence-transformers/all-MiniLM-L6-v2
 
 ## Usage
+
 ```python
 from huggingface_hub import hf_hub_download
 import torch
@@ -18,6 +60,34 @@ checkpoint = torch.load(model_path, map_location='cpu')
 ```
 
 ## Examples
-- "sweet vanilla scent" → Vanillin
-- "bitter coffee alkaloid" → Caffeine  
-- "minty cooling fresh" → Menthol
+
+| 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 ControlNet},
+  author={Hugging Face Community},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/munchers/scent-to-molecule}}
+}
+```