v0.1.5

Release Notes (v0.1.5)

v0.1.5

长期训练支持、编译兼容性及文档完善

• 支持长期连续训练：新增 beta2 参数。允许解除与训练步数的硬绑定，防止长序列训练中 EMA 窗口膨胀导致的优化器钝化。
• JIT 编译旁路开关：新增 use_cuda_kernel 参数。允许在无 CUDA 编译器环境中显式禁用 JIT 编译，直接回退至纯 PyTorch 实现，并修复了编译失败时的重试卡顿问题。
• 文档完善。

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Long Training Support, Compilation Compatibility & Documentation Improvements

• Support for long-term continual training: Added the beta2 parameter, which decouples the optimizer state from the hard-coded training step count, preventing optimizer "blunted" caused by EMA window inflation during long-sequence training.
• JIT compilation bypass switch: Added the use_cuda_kernel parameter. This allows explicitly disabling JIT compilation in environments without a CUDA compiler, falling back to a pure PyTorch implementation, and fixes the retry hang issue upon compilation failure.
• Documentation improvements.