Instructions to use machinelearningzuu/NER_PII_HF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use machinelearningzuu/NER_PII_HF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="machinelearningzuu/NER_PII_HF")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("machinelearningzuu/NER_PII_HF") model = AutoModelForTokenClassification.from_pretrained("machinelearningzuu/NER_PII_HF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad2f258cadc81a149ce653453152730f0e2010b39c27c4d140f1b70c5e0fe576
- Size of remote file:
- 431 MB
- SHA256:
- 496510297fc27c0858e7338fa05ed553b5c8cd8826666c17ea253c7f177c8052
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