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
Download tokenizer.json from kamalkraj/bert-base-cased-ner-conll2003: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/kamalkraj/bert-base-cased-ner-conll2003/resolve/refs%2Fpr%2F3/tokenizer.json
- Command line
-
hf download hf://kamalkraj/bert-base-cased-ner-conll2003@refs/pr/3/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/kamalkraj/bert-base-cased-ner-conll2003/resolve/refs%2Fpr%2F3/tokenizer.json
669 kB
File too large to display, you can check the raw version instead.