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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 665cad30eef7eda68f9c8d5da729cf1e2b84b4c4f6b5df7fc54ced380100bc7b
- Size of remote file:
- 17.5 MB
- SHA256:
- f11063ab296de73911abc220e5aeceff90836d0eaff4e2f70086fb80f6d11923
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