Comments (5)
SparkJiao
commented on September 4, 2024
下面链接是我们使用的Dataset，在config里有写明
https://github.com/dandelionsllm/pandallm/blob/main/data/collators/zh_instruct.py#L110C1-L136
可以按照这个Dataset处理你的数据，总体来说可以用jsonline存储，每一行是一个json结构体。如果你是instruction-response pair的数据，可以使用instruction和output两个filed来做conditional generation。如果你是pure text，希望做普通的causal LM，可以直接存到text这个key里。
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Cascol-Chen
commented on September 4, 2024
请问多个数据集要以什么树状结构进行存储呢，直接把用于训练的5个数据集压缩包解压到相同目录下就可以了吗
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SparkJiao
commented on September 4, 2024
不同的数据集均处理成上述结构之一，放在同一个目录下就行，config里写文件夹的path，glob会处理匹配（可以自己改glob的匹配方式）
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Cascol-Chen
commented on September 4, 2024
好的谢谢作者，我尝试一下
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Cascol-Chen
commented on September 4, 2024
在处理如百科数据时存在不知道该将title还是desc转为inputs的问题，请问有相关的转化脚本吗
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Related Issues (20)
- 感觉模型比原始的LlaMa模型大了很多，是什么原因 HOT 1
- 推理超参数 HOT 1
- 预训练和微调阶段使用的是全量微调还是lora? HOT 1
- 词表没扩充过是吗?还是32,000吧？ HOT 1
- linly预训练阶段和panda类似，指令微调阶段使用了500万条，为什么效果比panda差？ HOT 1
- 请问有使用的examples吗 HOT 1
- 权重转换脚本不支持来自 Facebook 的原版权重 HOT 2
- 请问如何在COIG数据集上继续训练 HOT 8
- 如何将COIG数据集处理为instruction tuning的格式 HOT 1
- 单卡A100训练7B模型OOM HOT 12
- 商用7b模型，直接进行推理说话毫无逻辑，难道不是开箱即用的嘛？ HOT 4
- 能否提供一下模型量化的方法？其他在mac上进行推理测试 HOT 1
- 由于训练数据的预处理存在不确定性，请问可以进一步分享处理代码吗 HOT 2
- 关于推理的问题 HOT 5
- RuntimeError: The size of tensor a (32000) must match the size of tensor b (32001) at non-singleton dimension 0 HOT 2
- Removed.
- Panda-LLaMA2-13B的模型链接不对吧？ HOT 3
- 在线体验需要访问密码？
- 在线体验 pandallm.ai/，该链接无法打开
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