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+ ---
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+ license: gpl-3.0
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+ language:
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+ - en
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+ widget:
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+ - text: "Sentence: We tried 4 different styles of donuts. The distribution of numerals in the sentence is equal to"
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+ example_title: "Example 1"
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+ - text: "Sentence: No one's going to take you seriously if they're full of typos. The distribution of subordinates in the sentence is equal to"
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+ example_title: "Example 2"
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+ ---
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+
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+ # Li-IT5 Small
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+
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+ <p align="center">
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+ <img src="lit5.png" alt="Linguistically-Informed T5" width="500"/>
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+ </p>
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+
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+
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+ This model is released as part of the paper "Linguistic Knowledge Can Enhance Encoder-Decoder Models (*If You Let It*)" (Miaschi et al., 2024).
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+ If you use this model in your work, we kindly ask you to cite our paper:
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+
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+ ```bibtex
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+ @inproceedings{miaschi_linguistic_knowledge,
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+ title = "Linguistic Knowledge Can Enhance Encoder-Deocer Models (If You Let It)",
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+ author = "Miaschi, Alessio and Dell'Orletta Felice and Venturi, Giulia",
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+ }
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+ ```
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+
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+ Other information can be found in the original [GitHub repository](https://github.com/alemiaschi/linguistically_informed_t5/tree/main).
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+
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+ ## Model Description
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+
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+ The model is based on a T5 model fine-tuned in a multitask fashion to solve a set of raw, morpho-syntactic and syntactic tasks (i.e. predictions of linguistic properties).
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+ The full list of the 10 linguistic properties used as intermediate tasks can be found in the original paper.
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+
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+ This model is based on the English version of t5-small, [t5-small](https://huggingface.co/google-t5/t5-small).
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+
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+ ## Model variations
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+
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+ The other fine-tuned models presented in the original study are the following:
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+
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+ - [li-it5-small](https://huggingface.co/alemiaschi/li-it5-small)
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+ - [li-it5-base](https://huggingface.co/alemiaschi/li-it5-base)