Instructions to use Jinchen/bert-base-uncased-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinchen/bert-base-uncased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Jinchen/bert-base-uncased-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Jinchen/bert-base-uncased-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Jinchen/bert-base-uncased-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cdc605d3f52ad3f0eeab5e2dfeb923c68cb968eb30072e6dbd85004172ef48b1
- Size of remote file:
- 2.67 kB
- SHA256:
- ec385bea5d0d9dc3b60909025d8eddb07f1ee00f4cd9aa8f5a499208f10b532f
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