Comments (10)
之前跑的是这个:https://github.com/mymusise/ChatGLM-Tuning/blob/master/finetune.py, 所以这个load 模型的部分应该是由优化的方法的吧?之前这个由于glm 模型升级后就不能跑了
from chatglm-6b-qlora.
你跑的是chatGLM2-6B吗?
我实测chatGLM2-6B在训练时内存占用明显高于chatGLM-6B,刚刚更新了README文件,做了说明。
在24G显存的情况下,per_device_batch_size设置为4可以正常跑下去,而chatGLM-6B,在12G显存的时候,都可以把per_device_batch_size调到8
关于这点,我也困惑中……
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@wujindou 看了下,我和他用的是一样的load方法,都是用peft库把8bit或4bit的模型加载进来
from chatglm-6b-qlora.
我跑的是chatglm6B,可能我这显存不太够,请教6b加载需要多少GPU?提示oom错误是在prepare_kbit时候
from chatglm-6b-qlora.
你跑的是chatGLM2-6B吗? 我实测chatGLM2-6B在训练时内存占用明显高于chatGLM-6B,刚刚更新了README文件,做了说明。 在24G显存的情况下,per_device_batch_size设置为4可以正常跑下去,而chatGLM-6B,在12G显存的时候,都可以把per_device_batch_size调到8 关于这点,我也困惑中……
这显存占用的问题太大了,输出质量高输入长度长固然很好,但是要优化还是得靠sft、ppo什么的,,,现在我单卡2k上下文啃都啃不动,而chatglm1代,轻松4k上下文
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@wujindou 不应该啊,我例子里那个数据集,如果使用chatglm-6b的话,一张RTX3060,12G的显存就能跑下来了,batchsize=8,刚开始占用8G多,后面11G多,但没有OOM
如果是chatglm2-6b的话,我用的24G的3090,batchsize=4,占用22G
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@starphantom666 你多大的显存?
from chatglm-6b-qlora.
@starphantom666 你多大的显存?
24G 4090
from chatglm-6b-qlora.
好像2代模型普遍存在这个问题:THUDM/ChatGLM2-6B#94
from chatglm-6b-qlora.
@starphantom666 @wujindou 2代模型已经修复了,拉最新的模型,主要是里面几个py文件,训练时显存占用和1代差不多
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Related Issues (20)
- 数据集格式instruction,input,output时tokenized出错 HOT 2
- 训练结束后,数据展示出现问题
- merge后模型Loading checkpoint shards Killed HOT 6
- 调优后的模型是否可以在CPU服务上部署? HOT 1
- protobuf 和 icetk 版本不兼容 HOT 1
- ImportError: libcudnn.so.8: cannot open shared object file: No such file or directory HOT 12
- RuntimeError: mat1 and mat2 shapes cannot be multiplied (588x4096 and 1x9437184) ,ChatGLM2-6B做微调,请问如何设置参数?? HOT 1
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0! (when checking argument for argument target in method wrapper_CUDA_nll_loss_forward),请问如何调整训练代码,适配多卡训练?? HOT 1
- transformers>4.30.2时,模型不会进行量化,是因为什么?
- BrokenPipeError: [Errno 32] Broken pipe HOT 7
- 训练结束后没有保存完整的adapter文件 HOT 2
- 用V100显卡微调chatglm2-6b,但是loss一直为0,eval_loss=nan
- 训练显存有些问题
- 微调后推理性能问题 HOT 1
- ChatGLM3-6B 微调报错 RuntimeError: CUDA error: invalid argument HOT 1
- ChatGLM2-6B微调后合并报错We need an `offload_dir` to dispatch this model according to this `device_map`, the following submodules need to be offloaded: HOT 2
- 合并模型的时候显存不够,用的4090,24G
- qlora微调训练随机性
- ValueError:
- ChatGLM2-6b模型合并时报错ValueError: We need an `offload_dir` to dispatch this model according to this `device_map`, the following submodules need to be offloaded
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