Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use worknick/bert-base-cased-finetuned-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use worknick/bert-base-cased-finetuned-conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="worknick/bert-base-cased-finetuned-conll2003")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("worknick/bert-base-cased-finetuned-conll2003") model = AutoModelForTokenClassification.from_pretrained("worknick/bert-base-cased-finetuned-conll2003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from worknick/bert-base-cased-finetuned-conll2003: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/worknick/bert-base-cased-finetuned-conll2003/resolve/main/training_args.bin
- Command line
-
hf download hf://worknick/bert-base-cased-finetuned-conll2003/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/worknick/bert-base-cased-finetuned-conll2003/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- e1a6e4c0251ec388720a305e740c1f6d0c5dc3e520439c3dc6b8b84abd82781a
- Size of remote file:
- 3.31 kB
- SHA256:
- 5bb888fa8c32b265145eeeb640f49788a0d8c5d9810f8a66b7b725b0105f3da7
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