Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use oyvindgrutle/ner-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyvindgrutle/ner-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oyvindgrutle/ner-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oyvindgrutle/ner-classification") model = AutoModelForTokenClassification.from_pretrained("oyvindgrutle/ner-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18d9775d6c2618b0571df00b301149a17e7f9b1ae6023d121c6a752fbca4b8b7
- Size of remote file:
- 3.31 kB
- SHA256:
- fc91d1c0330d2779f19317308e4cd1f8e3219f2645f6b2041b53adecc3c84549
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