Token Classification
Transformers
Safetensors
PyTorch
Hindi
bert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
hindi
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Hindi-BioClinicalBERT-Base-110M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Hindi-BioClinicalBERT-Base-110M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Hindi-BioClinicalBERT-Base-110M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Hindi-BioClinicalBERT-Base-110M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Hindi-BioClinicalBERT-Base-110M-v1") - Notebooks
- Google Colab
- Kaggle
File size: 206 Bytes
95a0350 | 1 2 3 4 5 6 7 8 | {
"epoch": 3.0,
"total_flos": 1680804629446656.0,
"train_loss": 0.23875660909233243,
"train_runtime": 122.3794,
"train_samples_per_second": 529.918,
"train_steps_per_second": 8.286
} |