Token Classification
Transformers
Safetensors
PyTorch
Portuguese
distilbert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
portuguese
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Portuguese-LiteClinicalU-Small-66M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Portuguese-LiteClinicalU-Small-66M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Portuguese-LiteClinicalU-Small-66M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Portuguese-LiteClinicalU-Small-66M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Portuguese-LiteClinicalU-Small-66M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload Portuguese PII detection model OpenMed-PII-Portuguese-LiteClinicalU-Small-66M-v1
f6b3999 verified | { | |
| "epoch": 3.0, | |
| "total_flos": 934111325716480.0, | |
| "train_loss": 1.9973642018636069, | |
| "train_runtime": 62.4241, | |
| "train_samples_per_second": 1153.401, | |
| "train_steps_per_second": 18.022 | |
| } |