Instructions to use townboy/kpfbert-kdpii with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use townboy/kpfbert-kdpii with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="townboy/kpfbert-kdpii")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("townboy/kpfbert-kdpii") model = AutoModelForTokenClassification.from_pretrained("townboy/kpfbert-kdpii") - Notebooks
- Google Colab
- Kaggle
| { | |
| "source_file": "연대1_PII_dataset_V3.json", | |
| "doc_count": 4981, | |
| "sentence_count": 53778, | |
| "examples_with_pii": 19037, | |
| "positive_ratio": 0.353992, | |
| "label_count": 33, | |
| "entity_count_by_label": { | |
| "PS_NAME": 2045, | |
| "PS_NICKNAME": 1354, | |
| "OGG_CLUB": 1269, | |
| "LC_PLACE": 1201, | |
| "CV_POSITION": 1166, | |
| "LC_ADDRESS": 1154, | |
| "OG_WORKPLACE": 1082, | |
| "OGG_EDUCATION": 1045, | |
| "OG_DEPARTMENT": 866, | |
| "QT_CARD_NUMBER": 805, | |
| "QT_ACCOUNT_NUMBER": 804, | |
| "DT_BIRTH": 734, | |
| "QT_PHONE": 713, | |
| "FD_MAJOR": 711, | |
| "QT_LENGTH": 707, | |
| "QT_AGE": 700, | |
| "QT_WEIGHT": 699, | |
| "TMI_EMAIL": 618, | |
| "LCP_COUNTRY": 613, | |
| "QT_MOBILE": 608, | |
| "PS_ID": 605, | |
| "QT_GRADE": 564, | |
| "OGG_RELIGION": 558, | |
| "CV_SEX": 553, | |
| "TM_BLOOD_TYPE": 467, | |
| "TMI_SITE": 460, | |
| "QT_PLATE_NUMBER": 457, | |
| "CV_MILITARY_CAMP": 407, | |
| "QT_DRIVER_NUMBER": 200, | |
| "QT_RESIDENT_NUMBER": 200, | |
| "QT_IP": 200, | |
| "QT_ALIEN_NUMBER": 200, | |
| "QT_PASSPORT_NUMBER": 200 | |
| }, | |
| "split_sentence_counts": { | |
| "train": 42894, | |
| "validation": 5463, | |
| "test": 5421 | |
| }, | |
| "split_doc_counts": { | |
| "train": 3984, | |
| "validation": 498, | |
| "test": 499 | |
| }, | |
| "seed": 42 | |
| } |