chore: import upstream snapshot with attribution
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wehub-resource-sync
2026-07-13 13:34:58 +08:00
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# 8 * 60GiB; 9s/it
# For ease of use, we use moonshotai/Moonlight-16B-A3B-Instruct, which is also based on the DeepseekV3ForCausalLM architecture.
# https://modelscope.cn/models/moonshotai/Moonlight-16B-A3B-Instruct/file/view/master/config.json?status=1
PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
NPROC_PER_NODE=8 \
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
megatron sft \
--model moonshotai/Moonlight-16B-A3B-Instruct \
--save_safetensors true \
--dataset 'liucong/Chinese-DeepSeek-R1-Distill-data-110k-SFT' \
--load_from_cache_file true \
--split_dataset_ratio 0.01 \
--pipeline_model_parallel_size 2 \
--decoder_last_pipeline_num_layers 13 \
--moe_permute_fusion true \
--expert_model_parallel_size 4 \
--moe_grouped_gemm true \
--moe_shared_expert_overlap true \
--moe_aux_loss_coeff 1e-3 \
--micro_batch_size 1 \
--global_batch_size 16 \
--packing true \
--recompute_granularity full \
--recompute_method uniform \
--recompute_num_layers 1 \
--num_train_epochs 1 \
--finetune true \
--cross_entropy_loss_fusion true \
--lr 1e-5 \
--lr_warmup_fraction 0.05 \
--min_lr 1e-6 \
--output_dir megatron_output/Moonlight-16B-A3B-Instruct \
--eval_steps 200 \
--save_steps 200 \
--max_length 8192 \
--dataloader_num_workers 8 \
--dataset_num_proc 8 \
--no_save_optim true \
--no_save_rng true \
--sequence_parallel true \
--attention_backend flash
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# 8 * 57GiB, 2.95s/it
PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
NPROC_PER_NODE=8 \
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
megatron sft \
--model Qwen/Qwen1.5-MoE-A2.7B \
--save_safetensors true \
--dataset 'liucong/Chinese-DeepSeek-R1-Distill-data-110k-SFT' \
--load_from_cache_file true \
--split_dataset_ratio 0.01 \
--pipeline_model_parallel_size 2 \
--decoder_last_pipeline_num_layers 11 \
--expert_model_parallel_size 4 \
--moe_permute_fusion true \
--moe_grouped_gemm true \
--moe_shared_expert_overlap true \
--moe_aux_loss_coeff 1e-3 \
--micro_batch_size 1 \
--global_batch_size 16 \
--packing true \
--moe_router_dtype fp32 \
--recompute_granularity full \
--recompute_method uniform \
--recompute_num_layers 1 \
--num_train_epochs 1 \
--finetune true \
--cross_entropy_loss_fusion true \
--lr 1e-5 \
--lr_warmup_fraction 0.05 \
--min_lr 1e-6 \
--output_dir megatron_output/Qwen1.5-MoE-A2.7B \
--eval_steps 200 \
--save_steps 200 \
--max_length 8192 \
--dataloader_num_workers 8 \
--dataset_num_proc 8 \
--no_save_optim true \
--no_save_rng true \
--sequence_parallel true \
--attention_backend flash \
--overlap_param_gather true \
--overlap_grad_reduce true
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# ZeRO3: 91.2s/it; 16 * 80GiB
# Megatron-LM: 9.6s/it; 16 * 60GiB
# Launch using Alibaba Cloud DLC
# https://help.aliyun.com/zh/pai/user-guide/general-environment-variables
# ref: https://github.com/modelscope/ms-swift/blob/main/examples/train/multi-node/dlc/train.sh
PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
NNODES=$WORLD_SIZE \
NODE_RANK=$RANK \
megatron sft \
--model Qwen/Qwen3-30B-A3B-Base \
--save_safetensors true \
--dataset 'liucong/Chinese-DeepSeek-R1-Distill-data-110k-SFT' \
--load_from_cache_file true \
--split_dataset_ratio 0.01 \
--pipeline_model_parallel_size 2 \
--expert_model_parallel_size 8 \
--moe_permute_fusion true \
--moe_grouped_gemm true \
--moe_shared_expert_overlap true \
--moe_aux_loss_coeff 1e-3 \
--micro_batch_size 1 \
--global_batch_size 16 \
--packing true \
--recompute_granularity full \
--recompute_method uniform \
--recompute_num_layers 1 \
--num_train_epochs 3 \
--finetune true \
--cross_entropy_loss_fusion true \
--lr 1e-5 \
--lr_warmup_fraction 0.05 \
--min_lr 1e-6 \
--output_dir megatron_output/Qwen3-30B-A3B-Base \
--eval_steps 200 \
--save_steps 200 \
--max_length 8192 \
--dataloader_num_workers 8 \
--dataset_num_proc 8 \
--no_save_optim true \
--no_save_rng true \
--sequence_parallel true \
--attention_backend flash
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# 28s/it; 4 * 75GiB
PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' \
NPROC_PER_NODE=4 \
CUDA_VISIBLE_DEVICES=0,1,2,3 \
megatron sft \
--model Qwen/Qwen3-30B-A3B-Base \
--save_safetensors true \
--dataset 'liucong/Chinese-DeepSeek-R1-Distill-data-110k-SFT' \
--load_from_cache_file true \
--split_dataset_ratio 0.01 \
--expert_model_parallel_size 4 \
--moe_permute_fusion true \
--moe_grouped_gemm true \
--moe_shared_expert_overlap true \
--moe_aux_loss_coeff 1e-3 \
--micro_batch_size 1 \
--global_batch_size 16 \
--packing true \
--recompute_granularity full \
--recompute_method uniform \
--recompute_num_layers 1 \
--finetune true \
--cross_entropy_loss_fusion true \
--lr 1e-5 \
--lr_warmup_fraction 0.05 \
--min_lr 1e-6 \
--output_dir megatron_output/Qwen3-30B-A3B-Base \
--eval_steps 200 \
--save_steps 200 \
--max_length 8192 \
--num_train_epochs 3 \
--dataloader_num_workers 8 \
--dataset_num_proc 8 \
--no_save_optim true \
--no_save_rng true \
--sequence_parallel true \
--optimizer_cpu_offload true \
--use_precision_aware_optimizer true \
--optimizer_offload_fraction 1 \
--attention_backend flash