

# BERT_SMILES_LARGE

This model is a 83.5M parameter ROBERTA model fine tuned on a dataset of 1.1M SMILES (Simplified molecular-input line-entry system) for masked language modeling (MLM). This model builds on BERT_SMILES which was fine tuned on only 50k SMILES. 

Example: 

Morphine

```
CN1CC[C@]23[C@@H]4[C@H]1CC5=C2C(=C(C=C5)O)O[C@H]3[C@H](C=C4)O
```

## Intended uses & limitations

This model can now be used to predict physical or chemical properties with further training. 

### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "widget": [{"text": "<mask>1CC[C@]23[C@@H]4[C@H]1CC5=C2C(=C(C=C5)O)O[C@H]3[C@H](C=C4)O"}], "pipeline_tag": "fill-mask", "model-index": [{"name": "ROBERTA_SMILES_LARGE", "results": []}]}
transformers tensorboard safetensors roberta fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us