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@@ -55,7 +55,5 @@ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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  ## More information about long-t5-tglobal-xl-16384-book-summary
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  - This is an 8-bit quantized version of `pszemraj/long-t5-tglobal-xl-16384-book-summary`.
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- - It generalizes reasonably well to academic and narrative text, producing high-quality summaries.
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- - The XL checkpoint is used, resulting in even better summaries from a human evaluation perspective.
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- - A simple example/use case with the base model on ASR can be found [here](https://huggingface.co/pszemraj/long-t5-tglobal-xl-16384-book-summary/tree/main/examples/asr).
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- - A proof-of-concept example using the infamous Navy Seals copypasta demonstrates the model's ability to generate summaries from even short text inputs.
 
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  ## More information about long-t5-tglobal-xl-16384-book-summary
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  - This is an 8-bit quantized version of `pszemraj/long-t5-tglobal-xl-16384-book-summary`.
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+ - It generalizes reasonably well to academic and narrative text.
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+ - The XL checkpoint is used, resulting in even better summaries from a human evaluation perspective.