Starbucks Coffee Company CTO Deb Hall Lefevre explains why architecture is strategy for modern businesses looking to compete in the technology age.

本研究提出了一种新颖的自我训练方法GiFT，旨在解决代码生成中描述与代码空间不足的问题。GiFT基于Gibbs抽样，从联合空间的边际分布中提取自生成数据，减轻条件抽样偏见。实验结果表明，该方法在多个数据集上表现优越，尤其在挑战性基准测试中效果显著。

本文探讨了数据集蒸馏的多种方法及应用，提出使用合成标签和元学习算法以提升模型性能。研究表明，软标签在数据集精馏中具有显著优势，并强调损失函数选择的重要性。新方法GIFT有效提升了数据集蒸馏效果，且不增加计算成本。

最近的研究表明，使用预训练教师模型生成的软标签在数据集蒸馏中具有优势。本文提出了一种新的方法GIFT，通过优化软标签和使用余弦相似性的损失函数，充分利用标签信息。实验证明，GIFT方法在各种规模的数据集蒸馏中提升了性能。

GIFT 是一种生成可解释化微调 Transformers 预训练模型的方法，在参数高效的情况下提供内置可解释性，通过选择 Transformer 模型的多头自注意力中的最终投影（线性）层进行 fine-tuning，提出了使用参数到聚类注意力来生成 fine-tuning 参数的超级 Transformer 方法，并在 VTAB 和 FGVC 基准测试中达到了显著更好的性能。

9 holiday gift ideas for open source enthusiasts in 2022 Opensource.com Fri, 11/25/2022 - 03:00 What do you get the open source enthusiast that has everything? More open source, of course! We...

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