Instructions to use gpancardo/mdeberta-pii with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gpancardo/mdeberta-pii with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="gpancardo/mdeberta-pii")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("gpancardo/mdeberta-pii") model = AutoModelForTokenClassification.from_pretrained("gpancardo/mdeberta-pii", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09276c12afb6b64ef0fe553eb9d092effe9fcdf0292a746be693a157b225dd4f
- Size of remote file:
- 4.31 MB
- SHA256:
- 13c8d666d62a7bc4ac8f040aab68e942c861f93303156cc28f5c7e885d86d6e3
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