wehub-resource-sync
52 lines
1.4 KiB
Bash
52 lines
1.4 KiB
Bash
top_k=64
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max_prompt_length=2048
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max_completion_length=2048
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max_total_length=$((max_prompt_length + max_completion_length))
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export IMAGE_MAX_TOKEN_NUM=1024
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# Teacher server must be running first:
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# CUDA_VISIBLE_DEVICES=0 \
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# swift deploy \
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# --model Qwen/Qwen3.5-4B \
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# --infer_backend vllm \
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# --port 8000 \
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# --max_logprobs $top_k \
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# --max_length $max_total_length \
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# --vllm_max_model_len $max_total_length
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NPROC_PER_NODE=4 \
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CUDA_VISIBLE_DEVICES=0,1,2,3 \
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PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
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swift rlhf \
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--rlhf_type gkd \
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--model Qwen/Qwen3.5-4B \
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--teacher_model_server http://localhost:8000 \
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--gkd_logits_topk $top_k \
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--use_vllm true \
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--vllm_mode colocate \
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--vllm_gpu_memory_utilization 0.5 \
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--vllm_tensor_parallel_size 1 \
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--vllm_max_model_len $max_total_length \
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--sleep_level 0 \
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--dataset 'modelscope/gsm8k' \
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--lmbda 1 \
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--beta 0.5 \
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--torch_dtype bfloat16 \
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--per_device_train_batch_size 2 \
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--gradient_accumulation_steps 4 \
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--learning_rate 5e-5 \
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--logging_steps 1 \
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--save_steps 100 \
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--save_total_limit 2 \
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--max_length $max_prompt_length \
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--max_completion_length $max_completion_length \
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--warmup_ratio 0.1 \
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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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--temperature 1.0 \
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--attn_impl flash_attn \
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--report_to tensorboard swanlab
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