Token Classification
Transformers
ONNX
Safetensors
English
Irish
distilbert
pii
de-identification
ireland
irish
gaelic
ppsn
eircode
phone-number
iban
passport
quantized
release-candidate
Instructions to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc2 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-rc2 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-rc2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc2") model = AutoModelForTokenClassification.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,040 Bytes
dfe9231 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | {
"recommended_thresholds": {
"ppsn_decoder": "word_aligned",
"ppsn_min_score": 0.5,
"other_min_score": 0.35,
"device": "cpu"
},
"comparison": {
"v1_public": {
"numeric_v2_f1": 0.3,
"gap_f1": 0.26666666666666666,
"core_f1": 0.9530201342281879,
"edge_f1": 0.5714285714285714,
"passport_numeric_v2_f1": 0.5,
"routing_numeric_v2_f1": 0.33333333333333337,
"phone_numeric_v2_f1": 0.0
},
"v2_rc1": {
"numeric_v2_f1": 0.21052631578947364,
"gap_f1": 0.13333333333333333,
"core_f1": 0.9487179487179489,
"edge_f1": 0.8205128205128205,
"passport_numeric_v2_f1": 0.0,
"routing_numeric_v2_f1": 0.0,
"phone_numeric_v2_f1": 0.5
},
"v2_rc2": {
"numeric_v2_f1": 0.896551724137931,
"gap_f1": 0.8695652173913043,
"core_f1": 0.9554140127388535,
"edge_f1": 0.9500000000000001,
"passport_numeric_v2_f1": 0.9090909090909091,
"routing_numeric_v2_f1": 1.0,
"phone_numeric_v2_f1": 0.75
}
}
}
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