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import os
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
kwargs = {
'per_device_train_batch_size': 2,
'save_steps': 5,
'gradient_accumulation_steps': 4,
'num_train_epochs': 1,
}
def test_llm():
from swift.llm import pt_main, TrainArguments, infer_main, InferArguments
result = pt_main(
TrainArguments(
model='Qwen/Qwen2-7B-Instruct', dataset=['swift/sharegpt:all#100'], split_dataset_ratio=0.01, **kwargs))
last_model_checkpoint = result['last_model_checkpoint']
infer_main(InferArguments(adapters=last_model_checkpoint, load_data_args=True, merge_lora=True))
def test_mllm():
from swift.llm import pt_main, TrainArguments, infer_main, InferArguments
result = pt_main(
TrainArguments(
model='Qwen/Qwen2-VL-7B-Instruct',
dataset=['modelscope/coco_2014_caption:validation#20', 'AI-ModelScope/alpaca-gpt4-data-en#20'],
split_dataset_ratio=0.01,
**kwargs))
last_model_checkpoint = result['last_model_checkpoint']
infer_main(InferArguments(adapters=last_model_checkpoint, load_data_args=True, merge_lora=True))
if __name__ == '__main__':
# test_llm()
test_mllm()
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