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:
- 39505e765f599400cdd021e2059504a840fc69c1e1483a4d69e73ba47d2439e2
- Size of remote file:
- 436 MB
- SHA256:
- 10f0a84a1c55e4738db0c45158e2022a5a39b711fbabace33ecc3683586cc54a
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