Instructions to use moo3030/roberta-for-pii with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moo3030/roberta-for-pii with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="moo3030/roberta-for-pii")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("moo3030/roberta-for-pii") model = AutoModelForTokenClassification.from_pretrained("moo3030/roberta-for-pii", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44711993b4427d670c0805dd7b4c1c646d21c546888b4d2e18ad6902dde5e588
- Size of remote file:
- 496 MB
- SHA256:
- ec79d15d1f8f5b09a6bc06768b1e3fcbd6655529f2506db1c848b7f63c6cd5e7
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