Text Classification
Transformers
PyTorch
Arabic
t5
text2text-generation
Classification
ArabicT5
Text Classification
Instructions to use Hezam/ArabicT5_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hezam/ArabicT5_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hezam/ArabicT5_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Hezam/ArabicT5_Classification") model = AutoModelForSeq2SeqLM.from_pretrained("Hezam/ArabicT5_Classification") - Notebooks
- Google Colab
- Kaggle
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المغربيه متابعه تفاجا زوار موقع القناه الاولي المغربي
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# # Arabic text classification using deep learning (ArabicT5)
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الثقافي
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الحمد لله رب العالمين والصلاة والسلام على سيد المرسلين نبينا محمد وآله وصحبه أجمعين،وبعد:فإنه يجب على العبد أن يتجنب الذنوب كلها دقها وجلها صغيرها وكبيرها وأن يتعاهد نفسه بالتوبة الصادقة والإنابة إلى ربه. قال تعالى: (وَتُوبُوا إِلَى اللَّهِ جَمِيعًا أَيُّهَا الْمُؤْمِنُونَ لَعَلَّكُمْ تُفْلِحُونَ)النور 31.
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# # Arabic text classification using deep learning (ArabicT5)
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