在量化格式上，我们参考 Kimi-K2-Thinking 选用了 INT4 (W4A16)方案。这主要考虑到相比 FP4，INT4 在现有硬件（Pre-Blackwell 架构）上的支持更加广泛，并且业界已有成熟高效的 Marlin Kernel 实现。实验表明，在 1×32 量化 Scale 粒度下，INT4 动态范围充足、精度稳定，其性能与生态链路均已高度优化。作为工业界“足够好（Good ...

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🤗 diffusers implementation of the paper "Generative Modeling by Estimating Gradients of the Data Distribution" [Yang+ NeurIPS'19]. Ensure that the custom components are placed in each subfolder ...