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* [Dataset, training, and evaluation](https://github.com/golsun/DialogRPT)
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* [Colab Notebook Demo](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)
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We considered the following tasks and provided corresponding pretrained models.
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| `updown` | ... which gets more upvotes?
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| `width
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| `depth
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### Examples:
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* [Dataset, training, and evaluation](https://github.com/golsun/DialogRPT)
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* [Colab Notebook Demo](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)
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We considered the following tasks and provided corresponding pretrained models.
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| Model card | Description |
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| :-----------: | :----------- |
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| | **Given a context and its two human responses, predict...** |
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| [`microsoft/DialogRPT-updown`](https://huggingface.co/microsoft/DialogRPT-updown) | ... which gets more upvotes? |
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| [`microsoft/DialogRPT-width`](https://huggingface.co/microsoft/DialogRPT-width) | ... which gets more direct replies? |
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| [`microsoft/DialogRPT-depth`](https://huggingface.co/microsoft/DialogRPT-depth) | ... which gets longer follow-up thread? |
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| | **Given a context and one human response, distinguish it with...** |
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| [`microsoft/DialogRPT-human-vs-rand`](https://huggingface.co/microsoft/DialogRPT-human-vs-rand) | ... a random human response |
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| [`microsoft/DialogRPT-human-vs-machine`](https://huggingface.co/microsoft/DialogRPT-human-vs-machine) | ... a machine generated response |
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### Examples:
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