Instructions to use jonghyunlee/DrugLikeMoleculeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonghyunlee/DrugLikeMoleculeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jonghyunlee/DrugLikeMoleculeBERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jonghyunlee/DrugLikeMoleculeBERT") model = AutoModel.from_pretrained("jonghyunlee/DrugLikeMoleculeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Jonghyun Lee commited on
Commit ·
de18ff6
1
Parent(s): 76a693d
add tokenizer
Browse files- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +69 -0
special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
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{"do_lower_case": false, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "full_tokenizer_file": null, "model_max_length": 128, "tokenizer_file": null, "name_or_path": "data/drug/molecule_tokenizer", "tokenizer_class": "BertTokenizer"}
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vocab.txt
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