Comments (2)
你好感谢肯定😊,是的微调的时候需要遵守Yi模型微调的格式,但现在其实不用这么复杂,你可以参考https://github.com/01-ai/Yi-1.5?tab=readme-ov-file#fine-tuning 里面的提及的微调框架,使用这些微调框架会自动转换成该模型需要的数据集格式。
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你好ryx103,
您提到的‘数据中的特殊tag’并不是必要的,实际上要看训练代码对于数据集是如何进行处理的。比如针对于'chosen'的处理:
https://github.com/01-ai/Yi/blob/11d140d641d18e1190caad2d5170da3b76c9e4f6/finetune/utils/data/raw_datasets.py#L24
当然了,我们提供的finetune并没有持续的维护。在现在这个时间点,很多的训练框架都更新/维护的非常好,比如 https://github.com/hiyouga/LLaMA-Factory 。一般来说,SFT数据集会采用ShareGPT格式是更加通用的做法。
希望这能解答你的疑惑 :-)
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Related Issues (20)
- 4K上下文完全不够用啊,能出个16K的吗? HOT 3
- Quick start code HOT 1
- Inquiries about the AGIEval setup HOT 1
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- Will Yi-large be published in open source? HOT 1
- 对于发展方向,提点小建议 HOT 1
- `max_length` (=20) to control the generation length. HOT 1
- 请问yi-large考虑登录一些第三方分发平台吗 HOT 1
- Yi-1.5-9B指标没法复现 HOT 1
- Does Yi-1.5-Chat model use the standard CHATML template? HOT 1
- 需要34b-chat-16k 量化版本 HOT 4
- test
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- Fast tokenizer HOT 2
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