Instructions to use Mahmoud22/AraClassificationModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud22/AraClassificationModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud22/AraClassificationModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud22/AraClassificationModel") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud22/AraClassificationModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 946a1e961f04c1808e2635c7a974de61ff2090b1e0266dd3a1e73e01f5e015eb
- Size of remote file:
- 3.45 kB
- SHA256:
- 4ac84f0d040195747401ba7ff7bf0628ac550cb7240f5554b5eeda5f0ee039a8
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