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README.md
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MeRALiON-LLaMA-3-8B-Instruct achieves notable improvements over official Llama-3 base and instruction-tuned models, highlighting the impact of our continued pretraining strategies. Through techniques such as corpus mixing, replay to prevent forgetting, and careful model merging, this model not only enhances general reasoning capabilities but also excels across multilingual and domain-specific benchmarks. In addition, we employed an LLM-based evaluation pipeline to standardize the judging process across varied output formats, ensuring fair and consistent comparisons. Building on the robust instruction-following proficiency of Llama-3.1-8B, MeRALiON-LLaMA-3-8B-Instruct extends its strengths to Southeast Asian languages, including Chinese and Indonesian.
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### Key highlights from the evaluations include
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- **Cross-MMLU, Cross-LogiQA**: Enhanced reasoning and question-answering capabilities illustrate that continued pretraining improves multilingual understanding and accuracy over baseline Llama models.
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MeRALiON-LLaMA-3-8B-Instruct achieves notable improvements over official Llama-3 base and instruction-tuned models, highlighting the impact of our continued pretraining strategies. Through techniques such as corpus mixing, replay to prevent forgetting, and careful model merging, this model not only enhances general reasoning capabilities but also excels across multilingual and domain-specific benchmarks. In addition, we employed an LLM-based evaluation pipeline to standardize the judging process across varied output formats, ensuring fair and consistent comparisons. Building on the robust instruction-following proficiency of Llama-3.1-8B, MeRALiON-LLaMA-3-8B-Instruct extends its strengths to Southeast Asian languages, including Chinese and Indonesian.
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### **Key highlights from the evaluations include**:
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- **Cross-MMLU, Cross-LogiQA**: Enhanced reasoning and question-answering capabilities illustrate that continued pretraining improves multilingual understanding and accuracy over baseline Llama models.
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