Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use kamalkraj/bert-base-cased-ner-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamalkraj/bert-base-cased-ner-conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kamalkraj/bert-base-cased-ner-conll2003")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kamalkraj/bert-base-cased-ner-conll2003") model = AutoModelForTokenClassification.from_pretrained("kamalkraj/bert-base-cased-ner-conll2003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ad8f9423f41c68d933a620487f6eabd477933787af8183bbd25769e6f1cf10d
- Size of remote file:
- 431 MB
- SHA256:
- 76de138632f844dc00a9838695ee03698521cbc81690fe7a2157bf925cdba9a3
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