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import os |
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os.environ['CUDA_VISIBLE_DEVICES'] = '1' |
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kwargs = { |
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'per_device_train_batch_size': 2, |
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'save_steps': 5, |
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'gradient_accumulation_steps': 4, |
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'num_train_epochs': 1, |
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} |
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def test_llm(): |
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from swift.llm import rlhf_main, RLHFArguments, infer_main, InferArguments |
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result = rlhf_main( |
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RLHFArguments( |
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rlhf_type='dpo', |
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model='Qwen/Qwen2-7B-Instruct', |
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dataset=['hjh0119/shareAI-Llama3-DPO-zh-en-emoji#100'], |
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split_dataset_ratio=0.01, |
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**kwargs)) |
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last_model_checkpoint = result['last_model_checkpoint'] |
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infer_main(InferArguments(adapters=last_model_checkpoint, load_data_args=True, merge_lora=True)) |
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def test_mllm(): |
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from swift.llm import rlhf_main, RLHFArguments, infer_main, InferArguments |
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os.environ['MAX_PIXLES'] = f'{1280 * 28 * 28}' |
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result = rlhf_main( |
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RLHFArguments( |
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rlhf_type='dpo', |
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model='Qwen/Qwen2-VL-7B-Instruct', |
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dataset=['swift/RLAIF-V-Dataset#100'], |
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split_dataset_ratio=0.01, |
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dataset_num_proc=8, |
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max_pixels=512 * 512, |
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**kwargs)) |
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last_model_checkpoint = result['last_model_checkpoint'] |
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infer_main(InferArguments(adapters=last_model_checkpoint, load_data_args=True, merge_lora=True)) |
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def test_mllm_zero3(): |
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os.environ['CUDA_VISIBLE_DEVICES'] = '0,1' |
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os.environ['MAX_PIXLES'] = f'{1280 * 28 * 28}' |
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from swift.llm import rlhf_main, RLHFArguments, infer_main, InferArguments |
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rlhf_main( |
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RLHFArguments( |
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rlhf_type='dpo', |
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model='Qwen/Qwen2-VL-7B-Instruct', |
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dataset=['swift/RLAIF-V-Dataset#100'], |
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split_dataset_ratio=0.01, |
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dataset_num_proc=8, |
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max_pixels=512 * 512, |
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deepspeed='zero3', |
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**kwargs)) |
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if __name__ == '__main__': |
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test_mllm() |
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