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-mLiteClinical-Base-135M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload Portuguese PII detection model OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1
ee0a56f verified Download train_results.json from OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1/resolve/main/train_results.json
- Command line
-
hf download hf://OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1/train_results.json
-
curl -L -o train_results.json https://huggingface.co/OpenMed/OpenMed-PII-Portuguese-mLiteClinical-Base-135M-v1/resolve/main/train_results.json
205 Bytes
| { | |
| "epoch": 3.0, | |
| "total_flos": 897577612476416.0, | |
| "train_loss": 1.8009334665934245, | |
| "train_runtime": 103.0568, | |
| "train_samples_per_second": 698.644, | |
| "train_steps_per_second": 10.916 | |
| } |