I am working on a project where we have to classify customer calls into more than 10 categories. As the client wants everything locally I tried a few local LLMs. Gemma turned out to be the best model for this task. The classification accuracy is impressive, and the client is happy that I am using an American model.
replyI guess the client is American.
replyYou can partially tell by the tokeniser; which gives you some hint into the training corpus mix.
reply</div> is four Gemma4 tokens, but one Qwen3.6 token.
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replyLooks like we have a /r/localllama dweller here.
replyWhere do you find this information for each model?
replyWhen you look on HuggingFace.co at the files of a model, for each model you will see a file "tokenizer.json".
replyIn that file you can see all tokens and their corresponding numeric codes.
The tokenizers are included in the open s̶o̶u̶r̶c̶e̶ weights releases; you wouldn’t be able to use the weights without the corresponding encoder/decoder, in fact.
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