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RANK=8 deepspeed --num_gpus=8 --num_nodes=2 train.py \ --base_model <LLAMA-2> --micro_batch_size 4\ --wandb_run_name mora_math_r8 --lora_target_modules q_proj,k_proj,v_proj,o_proj,gate_proj,down_proj,up_proj \ --num_epochs 3 --deepspeed ds.config --wandb_project lora-math --lora_r $RANK --batch_size 128 \ --data_path meta-math/MetaMath \ --save_steps 3000 \ --learning_rate 3e-4 --mora_type 6 \ --logging_steps 5 --use_bf16 --use_16bit --use_mora readme中提供的指令需要将数据集处理成什么格式
RANK=8 deepspeed --num_gpus=8 --num_nodes=2 train.py \ --base_model <LLAMA-2> --micro_batch_size 4\ --wandb_run_name mora_math_r8 --lora_target_modules q_proj,k_proj,v_proj,o_proj,gate_proj,down_proj,up_proj \ --num_epochs 3 --deepspeed ds.config --wandb_project lora-math --lora_r $RANK --batch_size 128 \ --data_path meta-math/MetaMath \ --save_steps 3000 \ --learning_rate 3e-4 --mora_type 6 \ --logging_steps 5 --use_bf16 --use_16bit --use_mora
The text was updated successfully, but these errors were encountered:
这个脚本应该会自动从huggingface上下载对应的数据并进行预处理。
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RANK=8 deepspeed --num_gpus=8 --num_nodes=2 train.py \ --base_model <LLAMA-2> --micro_batch_size 4\ --wandb_run_name mora_math_r8 --lora_target_modules q_proj,k_proj,v_proj,o_proj,gate_proj,down_proj,up_proj \ --num_epochs 3 --deepspeed ds.config --wandb_project lora-math --lora_r $RANK --batch_size 128 \ --data_path meta-math/MetaMath \ --save_steps 3000 \ --learning_rate 3e-4 --mora_type 6 \ --logging_steps 5 --use_bf16 --use_16bit --use_mora
readme中提供的指令需要将数据集处理成什么格式
The text was updated successfully, but these errors were encountered: