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@@ -38,4 +38,17 @@ model = EncoderDecoderModel.from_pretrained("Goud/AraBERT-summarization-goud")
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  input_ids = tokenizer(article, return_tensors="pt", truncation=True, padding=True).input_ids
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  generated = model.generate(input_ids)[0]
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  output = tokenizer.decode(generated, skip_special_tokens=True)
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  input_ids = tokenizer(article, return_tensors="pt", truncation=True, padding=True).input_ids
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  generated = model.generate(input_ids)[0]
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  output = tokenizer.decode(generated, skip_special_tokens=True)
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+ ```
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+
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+ ## Citation Information
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+
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+ ```
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+ @inproceedings{
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+ issam2022goudma,
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+ title={Goud.ma: a News Article Dataset for Summarization in Moroccan Darija},
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+ author={Abderrahmane Issam and Khalil Mrini},
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+ booktitle={3rd Workshop on African Natural Language Processing},
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+ year={2022},
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+ url={https://openreview.net/forum?id=BMVq5MELb9}
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+ }
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  ```