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
- Xet hash:
- 87b16416db5c298891f9d346787d3b1e543eefe868d22589fab18460954c22cc
- Size of remote file:
- 90 MB
- SHA256:
- fe42674cb8844a2e087b581a0e54a8dca84173180b3e47cc82f629aa60bbb05c
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