2024-04-22 简化
2023-10-09 inital reward
模型 | 32精度 | 混合精度 | 16精度 | lora int8 | lora int4 | ptv2 |
---|---|---|---|---|---|---|
llama | √ | √ | √ | √ | √ | × |
llama2 | √ | √ | √ | √ | √ | × |
chatglm | √ | √ | √ | √ | √ | × |
chatglm2 | √ | √ | √ | √ | √ | × |
baichuan | √ | √ | √ | √ | √ | × |
baichuan2 | √ | √ | √ | √ | √ | × |
opt | √ | √ | √ | √ | √ | × |
moss | √ | √ | √ | √ | √ | × |
rwkv | √ | √ | √ | √ | √ | × |
tiger | √ | √ | √ | √ | √ | × |
qwen | √ | √ | √ | √ | √ | × |
internlm | √ | √ | √ | √ | √ | × |
gpt2 | √ | √ | √ | √ | √ | × |
xverse | √ | √ | √ | √ | √ | × |
openbuddy | √ | √ | √ | √ | √ | × |
{
"prompt": "\n\nHuman:你能描述如何清除笔记本计算机屏幕上的指纹和污垢的步骤吗?\n\nAssistant:是的,也许。为了清洁你的屏幕,你首先需要使用微纤维布或软溼布,轻轻地擦拭屏幕表面。接下来,你会想抓住一个软,无毛巾,微纤维清洁布,轻轻地擦回屏幕上去除指纹和污垢。\n\nHuman:我可以将伊索普罗素酒精喷射到布上,并以这种方式清洗它吗?\n\nAssistant:",
"response": " 是的,你可以这样做,以帮助布从屏幕上收集更多的污垢。 请确保始终使用干净的软布,而不是一块粗糙的、粗糙的或结构化的材料,并确保它是无毛布的。",
"chosen": " 是的,你可以这样做,以帮助布从屏幕上收集更多的污垢。 请确保始终使用干净的软布,而不是一块粗糙的、粗糙的或结构化的材料,并确保它是无毛布的。",
"rejected": " 是的,你可以直接将它喷射到布上。"
}
-
cd data && make_data_example.py
-
python data_utils.py
注: num_process_worker 为多进程制作数据 , 如果数据量较大 , 适当调大至cpu数量 dataHelper.make_dataset_with_args(data_args.train_file,mixed_data=False, shuffle=True,mode='train',num_process_worker=0)
# 制作数据
cd scripts
bash train_full.sh -m dataset
or
bash train_lora.sh -m dataset
or
bash train_ptv2.sh -m dataset
注: num_process_worker 为多进程制作数据 , 如果数据量较大 , 适当调大至cpu数量
dataHelper.make_dataset_with_args(data_args.train_file,mixed_data=False, shuffle=True,mode='train',num_process_worker=0)
# 全参数训练
bash train_full.sh -m train
# lora adalora ia3
bash train_lora.sh -m train
# ptv2
bash train_ptv2.sh -m train
- pytorch-task-example
- chatmoss_finetuning
- chatglm_finetuning
- chatglm2_finetuning
- t5_finetuning
- llm_finetuning
- llm_rlhf
- chatglm_rlhf
- t5_rlhf
- rwkv_finetuning
- baichuan_finetuning
- internlm_finetuning
- qwen_finetuning
- xverse_finetuning
- auto_finetuning
- aigc_serving
纯粹而干净的代码
reward_finetuning's People
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