Instructions to use shellypeng/bert-base-cased-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shellypeng/bert-base-cased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="shellypeng/bert-base-cased-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("shellypeng/bert-base-cased-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("shellypeng/bert-base-cased-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d93956e43e6be2aaa77189d7f27a4b2dfd2ece48c96e3a87e2442dab6fe4fe75
- Size of remote file:
- 5.37 kB
- SHA256:
- b80e66472427296bb2ee345bdddaa48ea8cff9c0b5086bd048fd5601ff327274
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