Text Classification
Transformers
PyTorch
Arabic
bert
text classification
arabic
poetry
text-embeddings-inference
Instructions to use Ammar-alhaj-ali/arabic-MARBERT-poetry-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammar-alhaj-ali/arabic-MARBERT-poetry-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ammar-alhaj-ali/arabic-MARBERT-poetry-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ammar-alhaj-ali/arabic-MARBERT-poetry-classification") model = AutoModelForSequenceClassification.from_pretrained("Ammar-alhaj-ali/arabic-MARBERT-poetry-classification") - Notebooks
- Google Colab
- Kaggle
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## Arabic MARBERT
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#### Model description
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**arabic-MARBERT-poetry-classification Model** is a poetry classification model that was built by fine-tuning the [MARBERT](https://huggingface.co/UBC-NLP/MARBERT) model. For the fine-tuning, I used [APCD: Arabic Poem Comprehensive Dataset](https://hci-lab.github.io/ArabicPoetry-1-Private/) that includes 23 labels (البسيط,الطويل,الكامل,الوافر,الخفيف,السريع,..).
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- arabic
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- poetry
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## Arabic MARBERT Poetry Classification Model
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#### Model description
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**arabic-MARBERT-poetry-classification Model** is a poetry classification model that was built by fine-tuning the [MARBERT](https://huggingface.co/UBC-NLP/MARBERT) model. For the fine-tuning, I used [APCD: Arabic Poem Comprehensive Dataset](https://hci-lab.github.io/ArabicPoetry-1-Private/) that includes 23 labels (البسيط,الطويل,الكامل,الوافر,الخفيف,السريع,..).
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