Token Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use Falah/arabic2023_ner_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falah/arabic2023_ner_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Falah/arabic2023_ner_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Falah/arabic2023_ner_model") model = AutoModelForTokenClassification.from_pretrained("Falah/arabic2023_ner_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5ceb8c75e02dbad14c89ee07ff8338a95c73586613b8cdf8d275d3c5aed0de1
- Size of remote file:
- 266 MB
- SHA256:
- ca68b79dd4e377712c55840763ec9e734d66bf8c6548b5920cd9d2e445bd8076
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