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1 model = Qwen2VLForConditionalGeneration.from_pretrained(
2 'path/to/your/Qwen2-VL-7B-Instruct',
3 torch_dtype='auto',
4 attn_implementation="flash_attention_2"
5 )
6
7 # merge lora adapter from Training Stage-1
8 lora_model_dir = 'qwen2vl_7b_var_lora1'
9 model = PeftModel.from_pretrained(model, model_id=lora_model_dir)
10 model = model.merge_and_unload()
11
12 # merge lora adapter from Training Stage-2
13 lora2_dir = 'qwen2vl_7b_var_select3_lora2'
14 model = PeftModel.from_pretrained(model, model_id=lora2_dir)
15 model = model.merge_and_unload()
16
17 model.generate()@article{chang2026abductivemllm,
title={AbductiveMLLM: Boosting Visual Abductive Reasoning Within MLLMs},
author={Chang, Boyu and Wang, Qi and Guo, Xi and Nan, Zhixiong and Yao, Yazhou and Zhou, Tianfei},
journal={arXiv preprint arXiv:2601.02771},
year={2026}
}