metadata
license: cc-by-4.0
datasets:
- HZBSolarOptics/MultiLayerThinFilms
metrics:
- mae
tags:
- science
- material
- inverse
- design
OptoLlama
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
python -m pip install torch
python -m pip install safetensors
Load Model Checkpoint
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.
