Instructions to use intpc/bert-base-cased-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intpc/bert-base-cased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="intpc/bert-base-cased-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("intpc/bert-base-cased-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("intpc/bert-base-cased-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a020d0b3c795552072bfaf0d4cad7ba1d7db022b196ada4efcfb518ac6328e1
- Size of remote file:
- 431 MB
- SHA256:
- 1efa2a403884432fe028215ded13b546a6df44524e0d4d7225a5f951171279f1
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