Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use thientran/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thientran/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="thientran/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("thientran/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("thientran/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c34d0a1426984c34f48f20cac1f87864d2a46242bf0286b0ddff6bd24af72e3
- Size of remote file:
- 431 MB
- SHA256:
- bd18a25335a364ffdddcd4d2be28c7afb2043a0ed39576a1d5956d43659ba900
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.