Instructions to use cp500/PII_annotator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cp500/PII_annotator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cp500/PII_annotator")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cp500/PII_annotator") model = AutoModelForTokenClassification.from_pretrained("cp500/PII_annotator") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64910b38951ef26542b81145d9568a30de483e94aea89d732777aa0de2204b0e
- Size of remote file:
- 735 MB
- SHA256:
- 9f1a21ee9e269efa7183499cddf46b7d6488fe11de60f3e74f55d0109aabc9f0
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