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:
- 8a6c8560a00ce4e91f2af64318f40f15a06ef93e0fcd6032c8d9b0984cbf7cf9
- Size of remote file:
- 541 MB
- SHA256:
- d0916e751b17926d28b89f8bac0230ae23f4da4c0f6e9454eed107c894b7bb61
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