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[GH-ISSUE #347] 请问:如何用r1模型微调或蒸馏自己的数据?还是用传统的lora? 官方好像没有介绍 #269
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Originally created by @alexhmyang on GitHub (Feb 10, 2025).
Original GitHub issue: https://github.com/deepseek-ai/DeepSeek-R1/issues/347
谢谢
@deepsicker commented on GitHub (Feb 10, 2025):
知识蒸馏是一种模型压缩技术,其核心思想是将大型教师模型的知识传递给较小的学生模型。具体而言,学生模型通过学习教师模型对输入数据的软标签(即概率分布),从而在保持较小规模的同时,尽可能接近教师模型的性能。这种方法常用于在资源受限的环境中部署高效模型
@KDD2018 commented on GitHub (Feb 11, 2025):
同问,另外,基于满血版R1微调或者蒸馏具体需要什么配置?
@wingjson commented on GitHub (Feb 12, 2025):
满血部署都得1个t显存。微调至少x2
@alexhmyang commented on GitHub (Feb 13, 2025):
https://github.com/unslothai/unsloth/issues/1668#issuecomment-2653262963
unsloth 微调效果不对,完全不可用,上面是 测试过程
@github-actions[bot] commented on GitHub (Mar 25, 2025):
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. If you believe this issue is still relevant, please leave a comment to keep it open. Thank you for your contributions!
@github-actions[bot] commented on GitHub (Apr 30, 2025):
false