Instructions to use annedirkson/BERT_embeddings_ADR_normalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annedirkson/BERT_embeddings_ADR_normalization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="annedirkson/BERT_embeddings_ADR_normalization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("annedirkson/BERT_embeddings_ADR_normalization") model = AutoModel.from_pretrained("annedirkson/BERT_embeddings_ADR_normalization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from annedirkson/BERT_embeddings_ADR_normalization: direct link, hf CLI and curl.
- Browser
- Download file 358 Bytes
-
https://huggingface.co/annedirkson/BERT_embeddings_ADR_normalization/resolve/main/tokenizer_config.json
- Command line
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hf download hf://annedirkson/BERT_embeddings_ADR_normalization/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/annedirkson/BERT_embeddings_ADR_normalization/resolve/main/tokenizer_config.json
358 Bytes
| {"do_lower_case": true, "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, "name_or_path": "BioSyn-master/Models/pybiobert2", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |