Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use nickprock/bert-finetuned-ner-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickprock/bert-finetuned-ner-ontonotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nickprock/bert-finetuned-ner-ontonotes")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nickprock/bert-finetuned-ner-ontonotes") model = AutoModelForTokenClassification.from_pretrained("nickprock/bert-finetuned-ner-ontonotes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70233ce7031eb267ba897f158dd4dd49c309e3814b5cc0b0f95219b8c1db33eb
- Size of remote file:
- 431 MB
- SHA256:
- 5ec459a3fa526bb0b6d8ec39145f50b2b1249dbdbea64dafb50bca5e7f9944e2
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