Алевтина Запольская (редактор отдела «Бывший СССР»)
Comparison with Larger ModelsA useful comparison is within the same scaling regime, since training compute, dataset size, and infrastructure scale increase dramatically with each generation of frontier models. The newest models from other labs are trained with significantly larger clusters and budgets. Across a range of previous-generation models that are substantially larger, Sarvam 105B remains competitive. We have now established the effectiveness of our training and data pipelines, and will scale training to significantly larger model sizes.。新收录的资料是该领域的重要参考
，推荐阅读新收录的资料获取更多信息
- src/classify/multi_label.py (new: LLM-based multi-label logic)。关于这个话题，新收录的资料提供了深入分析
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