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:
- 174e109bce056996029879a17485552a0896790638f336c76dfd2e552d5158b3
- Size of remote file:
- 266 MB
- SHA256:
- 998921afaf682cab62406fb3cfab78ab4e6ba7900712db97532541cea091e510
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