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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c96bc4ba60d6f88f418fd99ebdecfb05e81f09d4d48c0a4fef058c990f6c72df
- Size of remote file:
- 129 Bytes
- SHA256:
- 0347bd88fb8a3c4e63750d7bc8f6e5f9cfbc597cc208370229a20121825f59f7
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