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  # *SeaLLM-7B-v2* - Large Language Models for Southeast Asia
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  <p align="center">
 
 
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  <a href="https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5" target="_blank" rel="noopener"> ๐Ÿค— Tech Memo</a>
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  &nbsp;&nbsp;
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  <a href="https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B" target="_blank" rel="noopener"> ๐Ÿค— DEMO</a>
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  We introduce [SeaLLM-7B-v2.5](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5), the state-of-the-art multilingual LLM for Southeast Asian (SEA) languagesย ๐Ÿ‡ฌ๐Ÿ‡ง ๐Ÿ‡จ๐Ÿ‡ณ ๐Ÿ‡ป๐Ÿ‡ณ ๐Ÿ‡ฎ๐Ÿ‡ฉ ๐Ÿ‡น๐Ÿ‡ญ ๐Ÿ‡ฒ๐Ÿ‡พ ๐Ÿ‡ฐ๐Ÿ‡ญ ๐Ÿ‡ฑ๐Ÿ‡ฆ ๐Ÿ‡ฒ๐Ÿ‡ฒ ๐Ÿ‡ต๐Ÿ‡ญ. It is the most significant upgrade since [SeaLLM-13B](https://huggingface.co/SeaLLMs/SeaLLM-13B-Chat), with half the size, outperforming performance across diverse multilingual tasks, from world knowledge, math reasoning, instruction following, etc.
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  ### Highlights
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- * [SeaLLM-7B-v2.5](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5) outperforms GPT-3.5 on most knowledge benchmarks....
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- * It achieves 79.0 and 34.9 on GSM8K and MATH.
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  ### Release and DEMO
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  # *SeaLLM-7B-v2* - Large Language Models for Southeast Asia
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  <p align="center">
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+ <a href="https://seallm.github.io" target="_blank" rel="noopener">Technical Blog</a>
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+ &nbsp;&nbsp;
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  <a href="https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5" target="_blank" rel="noopener"> ๐Ÿค— Tech Memo</a>
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  &nbsp;&nbsp;
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  <a href="https://huggingface.co/spaces/SeaLLMs/SeaLLM-7B" target="_blank" rel="noopener"> ๐Ÿค— DEMO</a>
 
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  We introduce [SeaLLM-7B-v2.5](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5), the state-of-the-art multilingual LLM for Southeast Asian (SEA) languagesย ๐Ÿ‡ฌ๐Ÿ‡ง ๐Ÿ‡จ๐Ÿ‡ณ ๐Ÿ‡ป๐Ÿ‡ณ ๐Ÿ‡ฎ๐Ÿ‡ฉ ๐Ÿ‡น๐Ÿ‡ญ ๐Ÿ‡ฒ๐Ÿ‡พ ๐Ÿ‡ฐ๐Ÿ‡ญ ๐Ÿ‡ฑ๐Ÿ‡ฆ ๐Ÿ‡ฒ๐Ÿ‡ฒ ๐Ÿ‡ต๐Ÿ‡ญ. It is the most significant upgrade since [SeaLLM-13B](https://huggingface.co/SeaLLMs/SeaLLM-13B-Chat), with half the size, outperforming performance across diverse multilingual tasks, from world knowledge, math reasoning, instruction following, etc.
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  ### Highlights
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+ * [SeaLLM-7B-v2.5](https://huggingface.co/SeaLLMs/SeaLLM-7B-v2.5) outperforms GPT-3.5 and achieves 7B SOTA on most multilingual knowledge benchmarks for SEA languages (MMLU, M3Exam & VMLU).
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+ * It achieves 79.0 and 34.9 on GSM8K and MATH, surpassing GPT-3.5 in MATH.
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  ### Release and DEMO
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