| The repository is adapted based on: https://huggingface.co./chenxran/bart-smiles/tree/main | |
| ```python | |
| from transformers import AutoTokenizer, AutoModel, SequenceFeatureExtractor | |
| import torch | |
| from transformers import AutoTokenizer, AutoModel | |
| smiles = "CCC(=O)" | |
| tokenizer = AutoTokenizer.from_pretrained("./BARTSmiles/", add_prefix_space=True) | |
| inputs = tokenizer(smiles, return_tensors="pt", return_token_type_ids=False, add_special_tokens=True) | |
| model = AutoModel.from_pretrained('./BARTSmiles') | |
| model.eval() | |
| # Use a pipeline as a high-level helper | |
| from transformers import pipeline | |
| extractor = pipeline("feature-extraction", model=model, tokenizer=tokenizer) | |
| result = extractor(smiles, return_tensors=True, tokenize_kwargs={'return_token_type_ids':False}) | |
| ``` | |
| ## Citation | |
| @article{chilingaryan2022bartsmiles, | |
| title={Bartsmiles: Generative masked language models for molecular representations}, | |
| author={Chilingaryan, Gayane and Tamoyan, Hovhannes and Tevosyan, Ani and Babayan, Nelly and Khondkaryan, Lusine and Hambardzumyan, Karen and Navoyan, Zaven and Khachatrian, Hrant and Aghajanyan, Armen}, | |
| journal={arXiv preprint arXiv:2211.16349}, | |
| year={2022} | |
| } | |