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model : Port Minimax M2 from mainline (#907)
Co-authored-by: firecoperana <firecoperana>
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@@ -399,6 +399,7 @@ struct llm_tokenizer_bpe : llm_tokenizer {
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};
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break;
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case LLAMA_VOCAB_PRE_TYPE_GPT4O:
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case LLAMA_VOCAB_PRE_TYPE_MINIMAX_M2:
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regex_exprs = {
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// original regex from tokenizer.json
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// "[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]*[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?|[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]+[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
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@@ -1987,6 +1988,10 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
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tokenizer_pre == "grok-2") {
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pre_type = LLAMA_VOCAB_PRE_TYPE_GROK_2;
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clean_spaces = false;
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} else if (
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tokenizer_pre == "minimax-m2") {
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pre_type = LLAMA_VOCAB_PRE_TYPE_MINIMAX_M2;
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clean_spaces = false;
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} else {
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throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
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}
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