2023-12-12 23:44:23 +08:00
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# Copyright © 2023 Apple Inc.
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import argparse
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import numpy as np
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from pathlib import Path
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import torch
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Convert Mixtral weights to MLX.")
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parser.add_argument(
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"--model_path",
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type=str,
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default="mixtral-8x7b-32kseqlen/",
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help="The path to the Mixtral model. The MLX model weights will also be saved there.",
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)
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args = parser.parse_args()
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model_path = Path(args.model_path)
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2023-12-13 05:33:33 +08:00
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state = torch.load(str(model_path / "consolidated.00.pth"))
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2023-12-12 23:44:23 +08:00
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np.savez(
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str(model_path / "weights.npz"),
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**{k: v.to(torch.float16).numpy() for k, v in state.items()},
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)
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