Instructions to use NAMAA-Space/AraModernBert-Topic-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NAMAA-Space/AraModernBert-Topic-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NAMAA-Space/AraModernBert-Topic-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NAMAA-Space/AraModernBert-Topic-Classifier") model = AutoModelForSequenceClassification.from_pretrained("NAMAA-Space/AraModernBert-Topic-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93af74f2e691f7519e9577946711673a59ba85c0672e3d6db7c5cd20bc8dd896
- Size of remote file:
- 1.2 GB
- SHA256:
- 25e0a39bc5c35600dc5ab4e40b6e25af4466b7653afa9c28fe761724de9f78b5
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