Instructions to use vuminhtue/DistillBert_base_NER_PII200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vuminhtue/DistillBert_base_NER_PII200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vuminhtue/DistillBert_base_NER_PII200")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vuminhtue/DistillBert_base_NER_PII200") model = AutoModelForTokenClassification.from_pretrained("vuminhtue/DistillBert_base_NER_PII200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ddb6e917fc701ade99d592eaa4d853d0fe222bde1df191019150bfa4de96a16
- Size of remote file:
- 4.6 kB
- SHA256:
- a59549b9e28e750aa25c1cbe70607d0f86fc7c41496253f940e44c9567fe3022
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