Instructions to use UMCU/PII_RobBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UMCU/PII_RobBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="UMCU/PII_RobBERT", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("UMCU/PII_RobBERT", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("UMCU/PII_RobBERT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Token classification scores (answering the question: ***given** the span, to which class does it belong?*):
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```json
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"eval_AGE": {
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"f1": 0.958,
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"precision": 0.957,
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Token classification scores (answering the question: ***given** the span, to which class does it belong?*):
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```json
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{
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"eval_AGE": {
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"f1": 0.958,
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"precision": 0.957,
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