PANews reported on November 25th that, according to the Shanghai Securities News, the Artificial Intelligence Agency of Singapore (AISG) has abandoned the Meta Llama model in its latest Southeast Asian language proficiency model project, opting instead for Alibaba's Qwen architecture. To date, the Qwen series has been downloaded over 600 million times globally. It is reported that "Qwen-SEA-LION-v4," released by AISG on November 25th, ranks first in the Southeast Asian language proficiency rankings. Previously, open-source models, represented by Meta's Llama series, performed poorly when handling regional languages such as Indonesian, Thai, and Malay, severely limiting the development efficiency and performance of localized AI applications.PANews reported on November 25th that, according to the Shanghai Securities News, the Artificial Intelligence Agency of Singapore (AISG) has abandoned the Meta Llama model in its latest Southeast Asian language proficiency model project, opting instead for Alibaba's Qwen architecture. To date, the Qwen series has been downloaded over 600 million times globally. It is reported that "Qwen-SEA-LION-v4," released by AISG on November 25th, ranks first in the Southeast Asian language proficiency rankings. Previously, open-source models, represented by Meta's Llama series, performed poorly when handling regional languages such as Indonesian, Thai, and Malay, severely limiting the development efficiency and performance of localized AI applications.
Singapore's national AI project has abandoned Meta and switched to Alibaba's Qwen model.
PANews reported on November 25th that, according to the Shanghai Securities News, the Artificial Intelligence Agency of Singapore (AISG) has abandoned the Meta Llama model in its latest Southeast Asian language proficiency model project, opting instead for Alibaba's Qwen architecture. To date, the Qwen series has been downloaded over 600 million times globally. It is reported that "Qwen-SEA-LION-v4," released by AISG on November 25th, ranks first in the Southeast Asian language proficiency rankings. Previously, open-source models, represented by Meta's Llama series, performed poorly when handling regional languages such as Indonesian, Thai, and Malay, severely limiting the development efficiency and performance of localized AI applications.
Sorumluluk Reddi: Bu sitede yeniden yayınlanan makaleler, halka açık platformlardan alınmıştır ve yalnızca bilgilendirme amaçlıdır. MEXC'nin görüşlerini yansıtmayabilir. Tüm hakları telif sahiplerine aittir. Herhangi bir içeriğin üçüncü taraf haklarını ihlal ettiğini düşünüyorsanız, kaldırılması için lütfen service@support.mexc.com ile iletişime geçin. MEXC, içeriğin doğruluğu, eksiksizliği veya güncelliği konusunda hiçbir garanti vermez ve sağlanan bilgilere dayalı olarak alınan herhangi bir eylemden sorumlu değildir. İçerik, finansal, yasal veya diğer profesyonel tavsiye niteliğinde değildir ve MEXC tarafından bir tavsiye veya onay olarak değerlendirilmemelidir.
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