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@@ -313,6 +313,31 @@ You can also use the same code to split a document into batches of 4096, etc., a
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  See [train with a script](https://huggingface.co/docs/transformers/run_scripts) and [the summarization scripts](https://github.com/huggingface/transformers/tree/main/examples/pytorch/summarization)
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  * * *
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  ## Training procedure
 
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  See [train with a script](https://huggingface.co/docs/transformers/run_scripts) and [the summarization scripts](https://github.com/huggingface/transformers/tree/main/examples/pytorch/summarization)
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+ ### Is there an easier way to use this?
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+ I have created a python package utility for this reason. It's called [textsum](https://github.com/pszemraj/textsum), and you can use it to load models and summarize things in a few lines of code.
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+ ```sh
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+ pip install textsum
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+ ```
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+ Use `textsum` in python with this model:
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+ ```python
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+ from textsum.summarize import Summarizer
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+ summarizer = Summarizer(model_name_or_path="pszemraj/long-t5-tglobal-xl-16384-book-summary")
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+ # summarize a long string
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+ out_str = summarizer.summarize_string('This is a long string of text that will be summarized.')
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+ print(f'summary: {out_str}')
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+ ```
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+ This package provides easy-to-use interfaces for using summarization models on text documents of arbitrary length. Currently implemented interfaces include a python API, CLI, and a shareable demo app.
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+ For details, explanations, and docs, see the README (_linked above_) or the [wiki](https://github.com/pszemraj/textsum/wiki).
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  * * *
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  ## Training procedure