wehub-resource-sync
49 lines
1.5 KiB
Bash
49 lines
1.5 KiB
Bash
# 4 * 66GiB, 5s/it
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# Fine-tuning GLM-4.6V requires Transformers 5.0, or you can switch the model to 'ZhipuAI/GLM-4.5V'.
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PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
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NPROC_PER_NODE=4 \
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CUDA_VISIBLE_DEVICES=0,1,2,3 \
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megatron sft \
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--model ZhipuAI/GLM-4.6V \
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--save_safetensors true \
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--merge_lora true \
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--dataset 'AI-ModelScope/LaTeX_OCR:human_handwrite#5000' \
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--load_from_cache_file true \
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--tuner_type lora \
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--lora_rank 8 \
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--lora_alpha 32 \
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--target_modules all-linear \
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--sequence_parallel true \
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--freeze_llm false \
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--freeze_vit true \
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--freeze_aligner true \
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--packing true \
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--split_dataset_ratio 0.01 \
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--tensor_model_parallel_size 4 \
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--expert_tensor_parallel_size 1 \
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--expert_model_parallel_size 4 \
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--moe_permute_fusion true \
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--moe_grouped_gemm true \
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--moe_shared_expert_overlap true \
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--moe_aux_loss_coeff 1e-3 \
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--micro_batch_size 1 \
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--global_batch_size 2 \
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--recompute_granularity full \
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--recompute_method uniform \
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--recompute_num_layers 1 \
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--finetune true \
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--cross_entropy_loss_fusion true \
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--lr 1e-4 \
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--lr_warmup_fraction 0.05 \
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--min_lr 1e-5 \
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--num_train_epochs 1 \
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--output_dir megatron_output/GLM-4.6V \
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--eval_steps 200 \
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--save_steps 200 \
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--max_length 2048 \
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--dataloader_num_workers 8 \
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--dataset_num_proc 8 \
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--no_save_optim true \
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--no_save_rng true \
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--attention_backend flash
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