| import os |
|
|
| os.environ['CUDA_VISIBLE_DEVICES'] = '0,1' |
|
|
|
|
| def test_sft(): |
| from swift.megatron import MegatronSftArguments, megatron_sft_main |
| megatron_sft_main( |
| MegatronSftArguments( |
| mcore_model='Qwen2.5-3B-Instruct-mcore', |
| dataset=['AI-ModelScope/function-calling-chatml#10000'], |
| loss_scale='hermes', |
| split_dataset_ratio=0.01, |
| tensor_model_parallel_size=2, |
| tuner_type='lora', |
| recompute_granularity='full', |
| recompute_method='uniform', |
| recompute_num_layers=1, |
| |
| |
| train_iters=100, |
| modules_to_save=['word_embeddings', 'output_layer'], |
| eval_iters=5, |
| save_steps=5, |
| no_save_optim=True, |
| no_save_rng=True, |
| sequence_parallel=True, |
| finetune=True)) |
|
|
|
|
| def test_moe(): |
| from swift.megatron import MegatronSftArguments, megatron_sft_main |
| megatron_sft_main( |
| MegatronSftArguments( |
| mcore_model='Qwen1.5-MoE-A2.7B-mcore', |
| dataset=['AI-ModelScope/alpaca-gpt4-data-zh#5000'], |
| split_dataset_ratio=0.01, |
| moe_shared_expert_overlap=True, |
| moe_grouped_gemm=True, |
| tensor_model_parallel_size=2, |
| |
| tuner_type='lora', |
| recompute_granularity='full', |
| modules_to_save=['word_embeddings', 'output_layer'], |
| recompute_method='uniform', |
| recompute_num_layers=1, |
| |
| |
| train_iters=100, |
| eval_iters=5, |
| save_steps=5, |
| no_save_optim=True, |
| no_save_rng=True, |
| sequence_parallel=True, |
| finetune=True)) |
|
|
|
|
| def test_convert(): |
| from swift import ExportArguments, export_main |
| export_main( |
| ExportArguments( |
| mcore_adapter='megatron_output/vx-xxx/checkpoint-xxx', |
| to_hf=True, |
| test_convert_precision=True, |
| )) |
|
|
|
|
| def test_embedding(): |
| pass |
|
|
|
|
| def test_resume(): |
| pass |
|
|
|
|
| if __name__ == '__main__': |
| test_sft() |
| |
| |
|
|
