Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
ner
nlp
Eval Results (legacy)
Instructions to use harpertoken/harpertokenNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harpertoken/harpertokenNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="harpertoken/harpertokenNER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("harpertoken/harpertokenNER") model = AutoModelForTokenClassification.from_pretrained("harpertoken/harpertokenNER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d583e4084ce44ae872c2780ebd27c446f1830869a7faac61a8169b63a0d646e
- Size of remote file:
- 3.58 kB
- SHA256:
- 744551c03e654bed92ec2ed9e7381dcd61adcfa27bde4efbca3ecf6b02f52c5e
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