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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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[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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```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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input_text = "..." # The text you want summarized |
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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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# The string summary contains the tldr |
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``` |
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For more information, check out [this repository](https://github.com/VerleysenNiels/arxiv-summarizer) |
