Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use Tahsin/BERT-finetuned-conll2003-POS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tahsin/BERT-finetuned-conll2003-POS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tahsin/BERT-finetuned-conll2003-POS")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tahsin/BERT-finetuned-conll2003-POS") model = AutoModelForTokenClassification.from_pretrained("Tahsin/BERT-finetuned-conll2003-POS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bebf1b56e0023f003528f0ae20e7235397a143833da65b2fc563b3fdf276b89
- Size of remote file:
- 431 MB
- SHA256:
- 070c144000395a4b7a826a70d402c848433017c8af8936ad8367ad481e322360
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