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:
- 8efff572beecdf2b4694bb77fce22a3e2e57200d494039a6d4f0fc80ed855976
- Size of remote file:
- 5.37 kB
- SHA256:
- bdd97ddbc0953c35acba1ed9f16dbb6d5e2c9bd9d374182dc76ce7ce720c4b15
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