GPT-3.5 crashes when it thinks about useRalativeImagePath too much
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Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#2[flagged]
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#3[deleted]
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#4Could be that it doesn’t have tokens with high enough probabilities so it outputs nothing.
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#5> As a result, the model isn’t trained on understanding the useRalativeImagePath token, and so it outputs something that isn’t a valid token.
That isn't how LLMs generate tokens. Each step outputs a logit for each possible token in the tokenizer (100k in the case of GPT-3.5), then softmaxes the logits to covert them into probabilities, and samples from them depending on temperature to get the token to be used.
It's possible something in the tokenizer BPE merge process breaks due to the rare token, which can be verified offline using tiktoken. But if GPT-4 works, and since GPT-3.5 and GPT-4 use the same tokenizer, then that's likely not the issue.
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#6This is a glitch token [1]! As the article hypothesizes, they seem to occur when a word or token is very common in the original, unfiltered dataset that was used to make the tokenizer, but then removed from there before GPT-XX was trained. This results in the LLM knowing nothing about the semantics of a token, and the results can be anywhere from buggy to disturbing.
A common example is usernames that participated on the r/counting subreddit, where some names appear hundreds of thousands of times. OpenAI has fixed most of them for the hosted models (not sure how, I could imagine by tokenizing them differently), but looks like you found a new one!
[1] https://www.lesswrong.com/posts/aPeJE8bSo6rAFoLqg/solidgoldm...
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#7> As a result, the model isn’t trained on understanding the useRalativeImagePath token, and so it outputs something that isn’t a valid token. That isn't how LLMs generate tokens. Each step outputs a logit for each possible token in the tokenizer (100k in the case of GPT-3.5), then softmaxes the logits to covert them into probabilities, and samples from them depending on temperature to get the token to be used. It's p…
Correct me if I'm wrong—but we don't know if GPT-4 uses the same tokenizer as GPT-3.5, right?
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#8> As a result, the model isn’t trained on understanding the useRalativeImagePath token, and so it outputs something that isn’t a valid token. That isn't how LLMs generate tokens. Each step outputs a logit for each possible token in the tokenizer (100k in the case of GPT-3.5), then softmaxes the logits to covert them into probabilities, and samples from them depending on temperature to get the token to be used. It's p…
Correct me if I'm wrong—but we don't know if GPT-4 uses the same tokenizer as GPT-3.5, right?
OpenAI's web tokenizer demo confirms it: https://platform.openai.com/tokenizer
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#9You could try putting this phrase in documents, to throw off attempts to summarize it with GPT-3.5. I asked ChatGPT to summarize this blog post
That screenshot reminded me of this old meme: https://knowyourmeme.com/memes/candlejack
Re: GPT-3.5 crashes when it thinks about useRalativeImagePath too much
#10That doesn't look like anything to me.