Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use naufalso/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naufalso/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="naufalso/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("naufalso/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("naufalso/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d63324c7ed10ab36c0c2cff94292e7342094961c7a923c775e5f86020d4c87cb
- Size of remote file:
- 431 MB
- SHA256:
- d3bc19aff56c901b62ea219a0d09518508d8f5d4c4d0f6ea88f1fc5aec34fdf1
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