Instructions to use commanderstrife/ADE-Bio_ClinicalBERT-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use commanderstrife/ADE-Bio_ClinicalBERT-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="commanderstrife/ADE-Bio_ClinicalBERT-NER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("commanderstrife/ADE-Bio_ClinicalBERT-NER") model = AutoModelForTokenClassification.from_pretrained("commanderstrife/ADE-Bio_ClinicalBERT-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 387 Bytes
46f31c1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": true,
"mask_token": "[MASK]",
"name_or_path": "emilyalsentzer/Bio_ClinicalBERT",
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"special_tokens_map_file": null,
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
|