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《哈萨比斯：谷歌AI之脑》（The Infinity Machine：Demis Hassabis, DeepMind, and the Quest for Superintelligence） 作者：[美]塞巴斯蒂安·马拉比（Sebastian Mallaby）译者：周健工
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Tokenizer EfficiencyThe Sarvam tokenizer is optimized for efficient tokenization across all 22 scheduled Indian languages, spanning 12 different scripts, directly reducing the cost and latency of serving in Indian languages. It outperforms other open-source tokenizers in encoding Indic text efficiently, as measured by the fertility score, which is the average number of tokens required to represent a word. It is significantly more efficient for low-resource languages such as Odia, Santali, and Manipuri (Meitei) compared to other tokenizers. The chart below shows the average fertility of various tokenizers across English and all 22 scheduled languages.
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