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@@ -22,10 +22,10 @@ Therefore, in order for the models to distinguish them from each other, a mark w
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  ## Info
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  Model trained using flax on huge dataset with jokes and anekdots on different tasks:
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  1. Span masks (dataset size: 850K)
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- 2. Conditional generation: generate inspiration by given setup (dataset size: 230K)
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- 3. Conditional generation: generate punch by given setup and inspiration (dataset size: 240K)
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- 4. Conditional generation: generate mark by given setup and punch (dataset size: 200K)
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  ## Ethical considerations and risks
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  Model is fine-tuned on a large corpus of humorous text data scraped from from websites/telegram channels with anecdotes, shortliners, jokes.
 
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  ## Info
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  Model trained using flax on huge dataset with jokes and anekdots on different tasks:
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  1. Span masks (dataset size: 850K)
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+ 2. Conditional generation tasks (simultaneously):
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+ a. Generate inspiration by given setup (dataset size: 230K)
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+ b. Generate punch by given setup and inspiration (dataset size: 240K)
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+ c. Generate mark by given setup and punch (dataset size: 200K)
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  ## Ethical considerations and risks
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  Model is fine-tuned on a large corpus of humorous text data scraped from from websites/telegram channels with anecdotes, shortliners, jokes.