Token Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use nickprock/distilbert-finetuned-ner-ontonotes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickprock/distilbert-finetuned-ner-ontonotes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="nickprock/distilbert-finetuned-ner-ontonotes")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("nickprock/distilbert-finetuned-ner-ontonotes") model = AutoModelForTokenClassification.from_pretrained("nickprock/distilbert-finetuned-ner-ontonotes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3598547274bcd7fb1297aa374a5409445b8bcd1dbc6fc3a95a253ceee6e752cc
- Size of remote file:
- 261 MB
- SHA256:
- 62fd5219a1716f42dd0c1b0985f2d6889b796987acadc9438e5f06f73a9525f5
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