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@@ -14,9 +14,6 @@ This model is trained to generate word definitions based on the word and a conte
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  using a subset of wordnet for all words that have an example and definition.
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  The model uses task prompts on the format 'define "[word]": [example sentence]'
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- To my knowledge, this is the first public model trained on a word definition task.
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- Similar work: [Zero-shot Word Sense Disambiguation using Sense Definition Embeddings](https://aclanthology.org/P19-1568.pdf)
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  This model in particular is a on-shot learner for unseen words, as it has to infer the definition by only one example
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  How to run:
 
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  using a subset of wordnet for all words that have an example and definition.
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  The model uses task prompts on the format 'define "[word]": [example sentence]'
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  This model in particular is a on-shot learner for unseen words, as it has to infer the definition by only one example
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  How to run: