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+ An Arabic abstractive text summarization model.
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+ A fine-tuned AraT5 model on a dataset that consists of 86,523 paragraph-summary pairs.
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+
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+ More details on the fine-tuning of this model will be released later.
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+
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+ The model can be used as follows:
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+ ```python
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+ from arabert.preprocess import ArabertPreprocessor
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+
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+ model_name="malmarjeh/t5-arabic-text-summarization"
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+ arabert_prep = ArabertPreprocessor(model_name=model_name)
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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+ pipeline = pipeline("text2text-generation",model=model,tokenizer=tokenizer)
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+
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+ text = "ولن نبالغ إذا قلنا إن هاتف أو كمبيوتر المكتب في زمننا هذا ضروري"
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+ preprocessor = ArabertPreprocessor(model_name="")
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+ preprocessor.preprocess(text)
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+ result = pipeline(text,
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+ pad_token_id=tokenizer.eos_token_id,
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+ num_beams=3,
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+ repetition_penalty=3.0,
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+ max_length=200,
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+ length_penalty=1.0,
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+ no_repeat_ngram_size = 3)[0]['generated_text']
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+ result
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+ >>>"و+ لن نبالغ إذا قل +نا إن هاتف أو كمبيوتر ال+ مكتب في زمن +نا هذا ضروري"
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+ ```