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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f34ddbe78c6e94f87a3a93a47156762811d14f3a5284a260b1aceb94c8f0539
- Size of remote file:
- 14.2 kB
- SHA256:
- 3e4e3f2c76c841a93a5381323cca8b4d90b8a05fa008a32306c4211971f113cc
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