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README.md
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#### Multilingual benchmarks
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<table>
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<tr>
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<td><strong>Benchmark</strong>
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</td>
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<td><strong>Language</strong>
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</td>
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<td><strong>Meta-Llama-3-8B </strong>
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</td>
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<td><strong>Meta-Llama-3-8B-quantized.w8a8 (this model)</strong>
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</td>
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<td><strong>Recovery</strong>
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</td>
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</tr>
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<tr>
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<td rowspan="9" ><strong>MMLU (5-shot, macro_avg/acc)</strong>
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</td>
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<td>Portuguese
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</td>
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<td>59.96
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</td>
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<td>59.36
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</td>
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<td>99.0%
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</td>
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</tr>
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<tr>
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<td>Spanish
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</td>
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<td>60.25
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</td>
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<td>59.77
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</td>
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<td>99.2%
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</td>
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</tr>
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<tr>
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<td>Italian
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</td>
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<td>59.23
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</td>
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<td>58.61
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</td>
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<td>99.0%
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</td>
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</tr>
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<tr>
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<td>German
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</td>
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<td>58.63
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</td>
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<td>58.23
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</td>
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<td>99.3%
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</td>
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</tr>
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<tr>
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<td>French
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</td>
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<td>59.65
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</td>
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<td>58.70
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</td>
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<td>98.4%
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</td>
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</tr>
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<tr>
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<td>Hindi
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</td>
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<td>50.10
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</td>
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<td>49.33
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</td>
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<td>98.5%
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</td>
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</tr>
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<tr>
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<td>Thai
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</td>
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<td>49.12
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</td>
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<td>48.09
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</td>
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<td>97.9%
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</td>
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</tr>
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</table>
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</tr>
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</table>
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