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@@ -27,6 +27,8 @@ The training dataset was a private collection of around 2000 jokes. This model h
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  See the example in the inference widget or How to use section for what constitues a narrative-style joke.
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  ### Install these first
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  You'll need to pip install transformers & maybe sentencepiece
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  See the example in the inference widget or How to use section for what constitues a narrative-style joke.
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+ For a slightly more accurate model (0.4% more) that is 65% slower at inference, see the [Deberta-v3 model](https://huggingface.co/Reggie/DeBERTa-v3-base-joke_detector). For a much more inaccurate model (2.4% less) that is way faster at inference, see the [distilbert model](https://huggingface.co/Reggie/distilbert-joke_detector).
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  ### Install these first
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  You'll need to pip install transformers & maybe sentencepiece
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