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24 lines
551 B
Python
24 lines
551 B
Python
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from transformers import AutoModelForCausalLM
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import numpy as np
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def replace_key(key: str) -> str:
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if key.startswith("transformer."):
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# remove transformer prefix
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key = key.replace("transformer.", "")
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return key
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def convert():
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model = AutoModelForCausalLM.from_pretrained(
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"Qwen/Qwen-1_8B", trust_remote_code=True
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)
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state_dict = model.state_dict()
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weights = {replace_key(k): v.numpy() for k, v in state_dict.items()}
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np.savez("weights.npz", **weights)
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if __name__ == "__main__":
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convert()
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