Transformers
PyTorch
Arabic
encoder-decoder
text2text-generation
AraBERT
BERT
BERT2BERT
MSA
Arabic Text Summarization
Arabic News Title Generation
Arabic Paraphrasing
Instructions to use abdalrahmanshahrour/ArabicSummarizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdalrahmanshahrour/ArabicSummarizer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abdalrahmanshahrour/ArabicSummarizer") model = AutoModelForSeq2SeqLM.from_pretrained("abdalrahmanshahrour/ArabicSummarizer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e36ead171daeacfe1c779267148e5359943be78cbef32a1c8c393cd66297ca6
- Size of remote file:
- 134 Bytes
- SHA256:
- 9de6d2e42231587a70b8b12937dab39e2feca662bb01a9b26159a7f80053338d
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