Token Classification
Transformers
ONNX
Safetensors
English
Irish
distilbert
pii
de-identification
ireland
ppsn
eircode
finance
passport
phone-number
multilingual
Eval Results (legacy)
Instructions to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1") model = AutoModelForTokenClassification.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 163 Bytes
d49b0d0 | 1 2 3 4 5 6 7 8 | {
"source_dir": "onnx/model.onnx",
"format": "onnx_dynamic_quantized",
"artifact": "model_quantized.onnx",
"weight_type": "QInt8",
"per_channel": true
}
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