Zek-Takai/glm53-flash-harvest

GLM-5.3-Flash On-Policy Harvest 86,006 responses / 246,034,910 generated tokens written by zai-org/GLM-5.3-Flash from its reference FP8 weights, across four harvest rounds, 15 registers and both serving modes (22,016 rows carry the model's inline <think>…</think> chain). It is on-policy text: the corpus records what the target model actually generates, which is what a speculative-decoding drafter (EAGLE-3 / DFlash / DSpark family) has to learn to predict. Everything here is MIT.… See the full description on the dataset page: https://huggingface.co/datasets/Zek-Takai/glm53-flash-harvest.