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from transformers import AutoModelForCausalLM |
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import torch |
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from modelscope import ( |
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snapshot_download, AutoModelForCausalLM, AutoTokenizer, GenerationConfig |
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) |
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import torch |
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model_id = 'qwen/Qwen-VL-Chat' |
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revision = 'v1.0.3' |
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|
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model_dir = snapshot_download(model_id, revision=revision) |
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model = AutoModelForCausalLM.from_pretrained(model_dir, device_map="auto", trust_remote_code=True, fp16=True).eval() |
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|
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state_dict = model.state_dict() |
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save_dict = {} |
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for k,v in state_dict.items(): |
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if 'visual' in k: |
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if 'transformer.visual.proj' not in k: |
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save_dict[k.replace('transformer.visual.', '')] = v |
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torch.save(save_dict, './qwen_clip/pytorch_model.bin') |
