What we’re now finding is that there’s a “continuum of glitchiness”. Some tokens glitch worse/harder than others in a way that I’ve devised an ad-hoc metric for (research report coming soon). There are a lot of “mildly glitchy” tokens that GPT-3 will try to avoid repeating which look like “velength” and “oldemort” (obviously parts of longer, familiar words, rarely seen isolated in text). There’s a long list of these in Part II of this post. I’d not seen “ocobo” or “oldemort” yet, but I’m systematically running tests on the whole vocabulary.
What we’re now finding is that there’s a “continuum of glitchiness”. Some tokens glitch worse/harder than others in a way that I’ve devised an ad-hoc metric for (research report coming soon). There are a lot of “mildly glitchy” tokens that GPT-3 will try to avoid repeating which look like “velength” and “oldemort” (obviously parts of longer, familiar words, rarely seen isolated in text). There’s a long list of these in Part II of this post. I’d not seen “ocobo” or “oldemort” yet, but I’m systematically running tests on the whole vocabulary.