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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.，这一点在Facebook亚洲账号,FB亚洲账号,海外亚洲账号中也有详细论述
Ранее был опубликован перечень регионов, где вторичное жилье подорожало наиболее значительно. Лидером стала Ленинградская область, где стоимость квадратного метра в готовых квартирах повысилась на 10,6% по результатам первого квартала 2026 года.，详情可参考有道翻译