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
Commit ·
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Parent(s): 11e8536
Update README.md
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README.md
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
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from arabert.preprocess import ArabertPreprocessor
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model_name="
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preprocessor = ArabertPreprocessor(model_name="")
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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```
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## Contact:
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<
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
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from arabert.preprocess import ArabertPreprocessor
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model_name="abdalrahmanshahrour/ArabicSummarizer"
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preprocessor = ArabertPreprocessor(model_name="")
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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```
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## Contact:
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<abdalrahman_shahrour@outlook.com>
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