点击上方“Deephub Imba”,关注公众号,好文章不错过 !这篇文章从头实现 LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures。需要说明的是,这里写的是一个简洁的最小化训练脚本,目标是了解 JEPA 的本质:对同一文本创建两个视图,预测被遮蔽片段的嵌入,用表示对齐损失来训练。本文的目标是 ...
这意味着在推理阶段,用户只需要提供问题描述,不需要任何关于简化规则的额外提示,模型就能自动生成既正确又简洁的代码。特别值得注意的是:ShortCoder的pass@100得分(0.967)超越了当前最先进的DeepSeek-Coder-6… ...
This library is not meant to stand-alone. Instead it defines common helpers used by all Google API clients. For more information, see the documentation. Python == 2.7, Python == 3.5, Python == 3.6.
Python turns 32. Explore 32 practical Python one-liners that show why readability, simplicity, and power still define the ...
JIT compiler stack up against PyPy? We ran side-by-side benchmarks to find out, and the answers may surprise you.
MT-DNN, an open-source natural language understanding (NLU) toolkit that makes it easy for researchers and developers to train customized deep learning models. Built upon PyTorch and Transformers, ...
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