Summarization
Transformers
PyTorch
Arabic
mbart
text2text-generation
AraBERT
BERT
BERT2BERT
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
Summarization
Generated from Trainer
Transformers
PyTorch
Instructions to use abdalrahmanshahrour/auto-arabic-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdalrahmanshahrour/auto-arabic-summarization with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="abdalrahmanshahrour/auto-arabic-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abdalrahmanshahrour/auto-arabic-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("abdalrahmanshahrour/auto-arabic-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f373a114387834734ee42ac53685017f3c1efd421d35228521b5f8ac4d78f9bb
- Size of remote file:
- 557 MB
- SHA256:
- c7397a91e0f2b6628f1a9fffddc1b07649f29decae03a45720687b27adc0cf05
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