wehub-resource-sync
43 lines
1.2 KiB
Bash
43 lines
1.2 KiB
Bash
# CUDA_VISIBLE_DEVICES=5 \
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# swift rollout \
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# --model Qwen/Qwen2.5-7B \
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# --vllm_max_model_len 2560
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# 4 * 54GiB
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# 5s/it (with vLLM)
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# 14s/it (without vLLM)
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NPROC_PER_NODE=4 \
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PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
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CUDA_VISIBLE_DEVICES=0,1,2,3 \
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swift rlhf \
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--rlhf_type gkd \
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--model Qwen/Qwen2.5-7B \
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--teacher_model Qwen/Qwen2.5-14B-Instruct \
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--tuner_type full \
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--dataset 'AI-ModelScope/alpaca-gpt4-data-en#2000' 'AI-ModelScope/alpaca-gpt4-data-zh#2000' \
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--split_dataset_ratio 0.01 \
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--lmbda 0.5 \
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--torch_dtype bfloat16 \
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--num_train_epochs 1 \
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--per_device_train_batch_size 4 \
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--per_device_eval_batch_size 4 \
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--learning_rate 1e-5 \
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--gradient_accumulation_steps 1 \
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--eval_steps 50 \
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--save_steps 50 \
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--save_total_limit 2 \
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--logging_steps 5 \
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--max_length 2048 \
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--max_completion_length 512 \
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--output_dir output \
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--warmup_ratio 0.05 \
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--save_only_model true \
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--dataloader_num_workers 4 \
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--dataset_num_proc 4 \
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--deepspeed zero3 \
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--attn_impl flash_attn \
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--use_vllm true \
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--vllm_mode server \
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--vllm_server_host 127.0.0.1 \
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--vllm_server_port 8000
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