Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use averageandyyy/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use averageandyyy/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="averageandyyy/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("averageandyyy/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("averageandyyy/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d42357715cbc771a0404b612c5e864bd1d5ebe0dcdc623b5f4a5e8a8071c8b0c
- Size of remote file:
- 431 MB
- SHA256:
- bc3b0c24a81754040aaacdfa5aeeb67587bfc193c1de3caaff19323e2c4de709
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