Longer GPT 3.5-turbo Output

[_j]

Are you sure not this the best for all models?

The models selectable vary greatly in perplexity, and the desired output of your application will also, and even the quality of a particular world language at a particular temperature will change, so there is no “best for all models”, you’re going to have some idea that will inform the choice better…

Questions regarding API sampling parameters (temperature, top_p)

Once one understands how the two parameters interplay, as I described in the first post, then one can use an intermix creatively, and there is no prohibition on using both at the same time. I would encourage considering some top_p reduction, because that removes the lottery-winning 0.001% token choices that make no sense or break code. A setting of the two parameters that is disparate and initially non-intuitive such as temperature = 2, top_p = 0.25 can satisfy creative writing desires - whi…

But the point is that - being the same model, and the one without the date being a “stable name” alias - setting the sampling parameters to where you don’t get random token outputs reveals the sameness of the models if you don’t simply trust the true model name returned from your API call.