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README.md

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 <img src="https://huggingface.co/datasets/ikala/tmmluplus/resolve/main/cover.png" alt="A close-up image of a neat paper note with a white background. The text 'TMMLU+' is written horizontally across the center of the note in bold, black. Join us to work in multimodal LLM : https://ikala.ai/recruit/" style="max-width: 400" width=400 />
 </p>
+We present TMMLU+, a traditional Chinese massive multitask language understanding dataset. TMMLU+ is a multiple-choice question-answering dataset featuring 66 subjects, ranging from elementary to professional level.
 
-We present TMMLU+ a traditional Chinese massive multitask language understanding dataset. TMMLU+ is a multiple-choice question-answering dataset with 66 subjects from elementary to professional level. 
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-TMMLU+ dataset is 6 times larger and contains more balanced subjects compared to the previous version, [TMMLU](https://github.com/mtkresearch/MR-Models/tree/main/TC-Eval/data/TMMLU). We included benchmark results in TMMLU+ from closed-source models and 20 open-weight Chinese large language models of parameters ranging from 1.8B to 72B. Benchmark results show Traditional Chinese variants still lag behind those trained on Simplified Chinese major models.
+The TMMLU+ dataset is six times larger and contains more balanced subjects compared to its predecessor, [TMMLU](https://github.com/mtkresearch/MR-Models/tree/main/TC-Eval/data/TMMLU). We have included benchmark results in TMMLU+ from closed-source models and 20 open-source Chinese large language models, with parameters ranging from 1.8B to 72B. The benchmark results show that Traditional Chinese variants still lag behind those trained on major Simplified Chinese models.
 
 
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