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+ ---
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+ datasets:
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+ - reddit
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+ metrics:
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+ - rouge
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+ ---
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+
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+ [Distilbart-cnn-6-6](https://huggingface.co/sshleifer/distilbart-cnn-6-6) finetuned on the [reddit dataset](https://huggingface.co/datasets/reddit)
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+ Example usage:
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+
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+ ```python
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+ # Load finetuned model
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+ tokenizer = BartTokenizer.from_pretrained("NielsV/distilbart-cnn-6-6-reddit")
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+ model = BartForConditionalGeneration.from_pretrained("NielsV/distilbart-cnn-6-6-reddit")
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+
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+ input_text = "..." # The text you want summarized
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+
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+ # Tokenize the text, summarize and decode the result
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+ inputs = tokenizer(input_txt, max_length=1024, return_tensors="pt")
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+ summary_ids = model.generate(inputs["input_ids"], num_beams=2, min_length=0, max_length=60)
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+ summary = tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
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+
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+ # The string summary contains the tldr
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+ ```
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+
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+ For more information, check out [this repository](https://github.com/VerleysenNiels/arxiv-summarizer)