Token Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use SakaiJun/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SakaiJun/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SakaiJun/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SakaiJun/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("SakaiJun/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2652909b715261817055a20af46f8803b520e4acb748ffceb59ea48ce2149ea
- Size of remote file:
- 431 MB
- SHA256:
- 54c7888103778ab2439b6b628e637ca0eb25f49ab89bd046b9c970990b1803c8
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