---
license: cc-by-4.0
datasets:
- HZBSolarOptics/MultiLayerThinFilms
metrics:
- mae
tags:
- science
- material
- inverse
- design
---
# OptoLlama
[](./LICENSE)
[](mailto:SE-AOPT-office@helmholtz-berlin.de)
Meet OptoLlama — a masked diffusion language transformer aimed to solve inverse design of multi-layer thin film structures.
**Key Features**
- Masked diffusion language model (**MDLM**)
- Support for reflectance, absorption and transmittance **RAT spectra** 📈
- Wave length from **300-2,000nm** 💡
- State-of-the-art **predictive performance** for inverse material design 😎
**Supporting Material**
**ArXiV Paper on MDLM**: 📝 https://arxiv.org/pdf/2406.07524
## Usage
### Install Dependencies
```bash
python -m pip install torch
python -m pip install safetensors
```
### Load Model Checkpoint
```python
from safetensors.torch import load_file
model = OptoLlama()
safetensors_path = "optollama-model.safetensors"
state_dict = load_file(safetensors_path)
model.load_state_dict(state_dict)
```
## Useful Information
| Stat | Value |
| :------------------ | ----------: |
| #Parameters | 111,555,513 |
| Best validation MAE | 0.0140 |
| top_p | 0.9 |
| top_k | 5 |
| Epochs trained | 1,000 |
| Best epoch | 866 |
| Batch size | 256 |
| n_blocks | 6 |
| n_heads | 8 |
| d_model | 1,024 |
| max_seq_length | 20 |
## Acknowledgements
This work is supported by the Helmholtz Association Initiative and Networking Fund through the Helmholtz AI platform, and the HAICORE@KIT grant.
----
