Use HF papers (#38184)
* Use hf papers * Hugging Face papers * doi to hf papers * style
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## Overview
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The PLBART model was proposed in [Unified Pre-training for Program Understanding and Generation](https://arxiv.org/abs/2103.06333) by Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang.
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The PLBART model was proposed in [Unified Pre-training for Program Understanding and Generation](https://huggingface.co/papers/2103.06333) by Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang.
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This is a BART-like model which can be used to perform code-summarization, code-generation, and code-translation tasks. The pre-trained model `plbart-base` has been trained using multilingual denoising task
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on Java, Python and English.
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@@ -50,7 +50,7 @@ model is multilingual it expects the sequences in a different format. A special
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source and target text. The source text format is `X [eos, src_lang_code]` where `X` is the source text. The
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target text format is `[tgt_lang_code] X [eos]`. `bos` is never used.
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However, for fine-tuning, in some cases no language token is provided in cases where a single language is used. Please refer to [the paper](https://arxiv.org/abs/2103.06333) to learn more about this.
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However, for fine-tuning, in some cases no language token is provided in cases where a single language is used. Please refer to [the paper](https://huggingface.co/papers/2103.06333) to learn more about this.
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In cases where the language code is needed, the regular [`~PLBartTokenizer.__call__`] will encode source text format
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when you pass texts as the first argument or with the keyword argument `text`, and will encode target text format if
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