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@@ -80,7 +80,7 @@ Obviously, this section is quite general as there are many things one can use "g
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  1. Correcting highly error-prone LM outputs. Some examples would be audio transcription (ASR) (this is literally some of the examples) or something like handwriting OCR.
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  - To be investigated further, depending on what model/system is used it _might_ be worth it to apply this after OCR on typed characters.
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  2. Correcting/infilling text generated by text generation models to be cohesive/remove obvious errors that break the conversation immersion. I use this on the outputs of [this OPT 2.7B chatbot-esque model of myself](https://huggingface.co/pszemraj/opt-peter-2.7B).
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- > An example of this in effect:
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  ```
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  original response:
 
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  1. Correcting highly error-prone LM outputs. Some examples would be audio transcription (ASR) (this is literally some of the examples) or something like handwriting OCR.
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  - To be investigated further, depending on what model/system is used it _might_ be worth it to apply this after OCR on typed characters.
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  2. Correcting/infilling text generated by text generation models to be cohesive/remove obvious errors that break the conversation immersion. I use this on the outputs of [this OPT 2.7B chatbot-esque model of myself](https://huggingface.co/pszemraj/opt-peter-2.7B).
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+ > An example of this model running on CPU with beam search:
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  ```
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  original response: