4 ms·
Neat. Is it a single under-trained token in GPT-5.2? Or is something else going on?
by skerit 7mo ago
Neat. Is it a single under-trained token in GPT-5.2? Or is something else going on?
- deleted 7mo ago[deleted]
- magicalhippo 7mo agoBased on their tokenizer tool[1], for GPT 5.x "geschniegelt" is tokenized into three tokens: (ges)(chn)(iegelt) [1]: https://platform.openai.com/tokenizer https://platform.openai.com/tokenizer
- Tiberium 7mo agoIt's a single token in the most common usage, that is, with a space in front of it "This word is geschniegelt" is [2500, 2195, 382, 192786] Last token here is " geschniegelt"
- nialv7 7mo agoMaybe this is why? Most of the training data has the single token version, so the three tokens version was undertrained?
- WatchDog 7mo agoPerhaps, the word does have it's own token, " geschniegelt"(geschniegelt with a space in front of it), is token 192786 in the tokenizer that GPT-5 apparently uses. https://raw.githubusercontent.com/niieani/gpt-tokenizer/refs/heads/main/data/o200k_base.tiktoken https://raw.githubusercontent.com/niieani/gpt-tokenizer/refs...
- nextaccountic 7mo agoIsn't giving this word a token something deeply wasteful? When some more common things are multiple tokens. Indeed, how do they deal with Chinese? Are some ideograms multiple tokens?
- mudkipdev 7mo agoIt simply means the tokenizer's training corpus may have included a massive amount of German literature or accidentally oversampled a web page where that word was frequently repeated. Look up "glitch tokens" to learn more.