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Autoregressive model can easily stuck into a loop and output repetitive contents due to its design. While some sampling settings such as temperature and top-p can help to alleviate the problem, other sampling methods/settings may be more effectively.
I believe that the generation code of the demo uses only the default OpenAI generation settings, i.e. temperature = 1 and top_p = 1 as they are not specified. There is current no support for params other than the default values, nor the use of presence_penalty and frequency_penalty which are both native to the API.
I think adding this feature would allow us to experiment with different settings, and choose the best one depending on user case to improve experience.
Suggested solution
Add sliders in the UI for temperature, top-p, presence_penalty, frequency_penalty
Clear and concise description of the problem
Autoregressive model can easily stuck into a loop and output repetitive contents due to its design. While some sampling settings such as temperature and top-p can help to alleviate the problem, other sampling methods/settings may be more effectively.
I believe that the generation code of the demo uses only the default OpenAI generation settings, i.e.
temperature = 1
andtop_p = 1
as they are not specified. There is current no support for params other than the default values, nor the use ofpresence_penalty
andfrequency_penalty
which are both native to the API.I think adding this feature would allow us to experiment with different settings, and choose the best one depending on user case to improve experience.
Suggested solution
temperature
,top-p
,presence_penalty
,frequency_penalty
Alternative
No response
Additional context
No response
Validations
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