Cut Cross Entropy

Cut Cross Entropy provides a highly memory-efficient implementation of the linear-cross-entropy loss function, primarily optimized for large language models and high-throughput inference scenarios. It is part of the vLLM project. The current version is 25.1.1, indicating a rapid development cycle, likely following a date-based or frequent release cadence, designed for NVIDIA GPUs.