Comments (8)
默认的配置我用了8个40GB的A100。
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2个40g就可以
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2个40g就可以
有开源吗?
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2个40g就可以
这个是用的原始的配置吗?我用 4 个 A00 仍然 GPU 不够, out of memory
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训练了多久呢?
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用dp zero 2, 长度拉小点一般256-512就够了,我用2个40g,4个3090 都测试过,可以跑,如果跑一半不可以,就可能是长度问题。
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2个40g就可以
这个是用的原始的配置吗?我用 4 个 A00 仍然 GPU 不够, out of memory
检查cpu的内存,不一定是显存不够
from finetune-chatglm2-6b.
用dp zero 2, 长度拉小点一般256-512就够了,我用2个40g,4个3090 都测试过,可以跑,如果跑一半不可以,就可能是长度问题。
麻烦能贴一下详细的参数配置吗,我用 4 卡 24G 的 A5000 一直爆显存, CPU 内存是 80G
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Related Issues (20)
- 请问全参数微调需要什么配置呢? HOT 9
- 请问这个项目的依赖是什么,安装的deepspeed版本好像跑不了。 HOT 1
- 模型训练,出现deepspeed_init() got an unexpected keyword argument 'resume_from_checkpoint' HOT 4
- 训练数据过多时报错Socket Timeout
- 请问这个问题怎么解决OSError: Can't get source for <function apply_rotary_pos_emb at 0x7fef8c15f790>. TorchScript requires source access in order to carry out compilation, make sure original .py files are available.
- --max_length 762,我想问一下这个是输入的最大长度吗,如果是,那么如果是多轮对话,有长度限制吗?
- max_len 768 这个长度在多轮对话中,是单次输入的长度,还是history+这次输入的长度? 如果是单次输入的长度,那么history的长度在哪里?
- 微调出来的模型可以直接用chatglm2官网发版的web_demo2.py来测吗,会有影响吗? HOT 1
- 我只有200多条多轮对话的数据,去做全参微调能有效果吗? HOT 2
- 微调时在runing tokenizer on train dataset这一步卡住 HOT 1
- ChatGLM数据处理中input_ids的padding问题
- 基于school_math_0.25M.json数据集进行微调训练后得到的模型推理效果很差,是什么原因?
- 请问可以训练chatGLM2-6B-32K的模型嘛
- do_eval时报错 HOT 1
- 多轮数据下载后要如何处理?
- CUDA out of memory. Tried to allocate 11.63 GiB (GPU 0; 23.69 GiB total capacity; 11.63 GiB already allocated; 11.28 GiB free HOT 1
- timed out HOT 1
- 模型训练,input_ids出现None type HOT 2
- 为什么不用新版本的transformer么?
- 有考虑 加入lora训练吗 HOT 1
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