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:
- 27356452c0a20967041bda21cf035f30073c0feea295610c9e6d47f916ff2e94
- Size of remote file:
- 541 MB
- SHA256:
- 63bc469866ac14afc191b989a948d44193f2c90de3ce3e26f4259a4a53f725ed
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