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Anthropomorphize your prompts. There is no substitute for screening out a number of prompts to see what distinct completions they elicit and to reverse-engineer what kind of text GPT-3 "thinks" a prompt arrived from, which may possibly not be what you intend and think (following all, GPT-3 just sees the few phrases of the prompt-it’s no more a telepath than you are). And there may be encodings which just do the job greater than BPEs, like unigrams (comparison) or CANINE or Charformer. OA’s GPT-f operate on utilizing GPT for MetaMath official theorem-proving notes that they use the typical GPT-2 BPE but "preliminary experimental results display attainable gains with specialized tokenization techniques." I ponder what other delicate GPT artifacts BPEs could be resulting in? This is certainly really a obtain, but it is a double-edged sword: it is confusing to write code for it mainly because the BPE encoding of a textual content is unfamiliar & unpredictable (introducing a letter can change the ultimate BPEs fully), and the consequences of obscuring the precise people from GPT are unclear

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Thus, logprobs can offer you extra insight when debugging a prompt than just continuously hitting ‘complete’ and receiving annoyed. I do not use logprobs a great deal but I typically use them in 1 of three means: I use them to see if the prompt ‘looks weird’ to GPT-3 to see the place in a completion it ‘goes off the rails’ (suggesting the have to have for decrease temperatures/topp or larger BO) and to peek at doable completions to see how unsure it is about the correct reply-a good example of that is Arram Sabeti’s uncertainty prompts investigation where the logprobs of every single attainable completion offers you an plan of how perfectly the uncertainty prompts are doing the job in receiving GPT-3 to place pounds on the right solution, or in my parity evaluation where by I observed that the logprobs of vs 1 were almost specifically 50:50 no issue how many samples I included, demonstrating no trace whatsoever of couple-shot discovering taking place. On our new weekly lightning round mini ep with Jonah Weiner, we’re fucking around with Barstool Sports, Complex Media, Jimmy and Larry, Jerry Seinfeld, the United States Department of Defense, Jeff Bezos, gorp, Substack subscribers, Visvim, And Wander, movie star profiles and much far more. I have not been able to exam no matter if GPT-3 will rhyme fluently presented a good encoding I have tried out a quantity of formatting methods, utilizing the International Phonetic Alphabet to encode rhyme-pairs at the beginning or conclusion of traces, annotated inside strains, house-separated, and non-IPA-encoded, but although GPT-3 is aware the IPA for additional English phrases than I would’ve anticipated, none of the encodings display a breakthrough in efficiency like with arithmetic/anagrams/acrostics