Token Classification
Transformers
Safetensors
PyTorch
English
bert
named-entity-recognition
ner
medical
disease-extraction
healthcare
clinical-bert
fine-tuned
bio-tagging
Instructions to use keanteng/bert-ner-wqd7005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keanteng/bert-ner-wqd7005 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="keanteng/bert-ner-wqd7005")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("keanteng/bert-ner-wqd7005") model = AutoModelForTokenClassification.from_pretrained("keanteng/bert-ner-wqd7005") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
This model has 1 file scanned as unsafe.