Token Classification
Transformers
ONNX
Safetensors
English
Irish
distilbert
pii
de-identification
ireland
irish
gaelic
ppsn
eircode
phone-number
iban
passport
quantized
release-candidate
Eval Results (legacy)
Instructions to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc4")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc4") model = AutoModelForTokenClassification.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc4") - Notebooks
- Google Colab
- Kaggle
| [project] | |
| name = "openmed-mliteclinical-irishcorepii-rc" | |
| version = "0.2.0rc3" | |
| description = "Third QA release candidate for Irish core PII detection with OpenMed mLiteClinical" | |
| requires-python = ">=3.10" | |
| readme = "README.md" | |
| license = { text = "Apache-2.0" } | |
| dependencies = [ | |
| "transformers>=4.41.0", | |
| "torch", | |
| "regex>=2024.5.15", | |
| "onnxruntime>=1.20.0", | |
| "numpy>=1.26.0", | |
| "huggingface_hub>=0.36.0", | |
| ] | |
| [tool.uv] | |
| package = false | |