Instructions to use jdavit/bert-finetuned-ner-19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jdavit/bert-finetuned-ner-19 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jdavit/bert-finetuned-ner-19")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jdavit/bert-finetuned-ner-19") model = AutoModelForTokenClassification.from_pretrained("jdavit/bert-finetuned-ner-19", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43d904ac38cfa564491ff56dc94060483abfff15913a09a71d35f5725a5c3e88
- Size of remote file:
- 5.11 kB
- SHA256:
- f11d533c12aa8a42f98b874d663fe27dc0cc8fe01b6fdbf0afba9256e8cf80ba
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