Token Classification
Transformers
Safetensors
PyTorch
English
bert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
hipaa
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-ClinicalE5-Base-109M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-ClinicalE5-Base-109M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-ClinicalE5-Base-109M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-ClinicalE5-Base-109M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-ClinicalE5-Base-109M-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "total_flos": 1.8767762625368064e+16, | |
| "train_loss": 0.1060635477882836, | |
| "train_runtime": 842.9188, | |
| "train_samples_per_second": 177.953, | |
| "train_steps_per_second": 5.563 | |
| } |