Token Classification
Transformers
TensorBoard
Safetensors
PyTorch
English
bert
BertForTokenClassification
named-entity-recognition
roberta-base
Generated from Trainer
Eval Results (legacy)
Instructions to use arnabdhar/bert-tiny-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arnabdhar/bert-tiny-ontonotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arnabdhar/bert-tiny-ontonotes")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arnabdhar/bert-tiny-ontonotes") model = AutoModelForTokenClassification.from_pretrained("arnabdhar/bert-tiny-ontonotes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d570b60c58c15fc03171d259f883dbf834670ce3c8c9eee70a38b644a536777
- Size of remote file:
- 4.73 kB
- SHA256:
- a73c8bd77b573e6809d8c77e8a018f2d6bfc19542e44e803a2ce065b83ae8cd0
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