| import os |
|
|
| os.environ['CUDA_VISIBLE_DEVICES'] = '0,1' |
|
|
|
|
| def test_embedding(): |
| from swift.megatron import MegatronSftArguments, megatron_sft_main |
| megatron_sft_main( |
| MegatronSftArguments( |
| model='Qwen/Qwen3-Embedding-0.6B', |
| task_type='embedding', |
| dataset=['sentence-transformers/stsb:positive'], |
| split_dataset_ratio=0.01, |
| micro_batch_size=4, |
| tensor_model_parallel_size=2, |
| tuner_type='lora', |
| num_train_epochs=1, |
| recompute_granularity='full', |
| recompute_method='uniform', |
| recompute_num_layers=1, |
| loss_type='infonce', |
| vit_attn_impl='flash_attn', |
| max_length=2048, |
| eval_iters=5, |
| save_steps=5, |
| no_save_optim=True, |
| no_save_rng=True, |
| sequence_parallel=True, |
| finetune=True)) |
|
|
|
|
| def test_reranker(): |
| from swift.megatron import MegatronSftArguments, megatron_sft_main |
| megatron_sft_main( |
| MegatronSftArguments( |
| model='Qwen/Qwen3-Reranker-4B', |
| tuner_type='lora', |
| load_from_cache_file=True, |
| num_train_epochs=1, |
| task_type='generative_reranker', |
| dataset=['MTEB/scidocs-reranking#2000'], |
| loss_type='pointwise_reranker', |
| split_dataset_ratio=0.01, |
| tensor_model_parallel_size=2, |
| recompute_granularity='full', |
| 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)) |
|
|
|
|
| if __name__ == '__main__': |
| test_embedding() |
| |
|
|
