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:
- b0ed3e9e0e14130fe76587137b34ea635138eb322a6c5bbdf3e06d2fa1d0db39
- Size of remote file:
- 3.52 kB
- SHA256:
- b8082196c156eaf17f402a51e9aea54ed662f5ad708f89154ff2e9d2a5c87d22
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