Instructions to use UMCU/PII_XMLR.eu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UMCU/PII_XMLR.eu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="UMCU/PII_XMLR.eu", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("UMCU/PII_XMLR.eu", trust_remote_code=True) model = AutoModelForTokenClassification.from_pretrained("UMCU/PII_XMLR.eu", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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End2End scores (answering the question: *given a text, what are the spans **and** to which class
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End2End scores (answering the question: *given a text, what are the spans **and** to which class do they belong?*):
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```json
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