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convert : fix tensors using grad in some models (#4173)
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@ -880,20 +880,21 @@ print(f"Loading model: {dir_model.name}")
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hparams = Model.load_hparams(dir_model)
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hparams = Model.load_hparams(dir_model)
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model_class = Model.from_model_architecture(hparams["architectures"][0])
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with torch.inference_mode():
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model_instance = model_class(dir_model, ftype_map[args.outtype], fname_out, args.bigendian)
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model_class = Model.from_model_architecture(hparams["architectures"][0])
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model_instance = model_class(dir_model, ftype_map[args.outtype], fname_out, args.bigendian)
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print("Set model parameters")
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print("Set model parameters")
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model_instance.set_gguf_parameters()
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model_instance.set_gguf_parameters()
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print("Set model tokenizer")
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print("Set model tokenizer")
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model_instance.set_vocab()
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model_instance.set_vocab()
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if args.vocab_only:
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if args.vocab_only:
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print(f"Exporting model vocab to '{fname_out}'")
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print(f"Exporting model vocab to '{fname_out}'")
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model_instance.write_vocab()
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model_instance.write_vocab()
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else:
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else:
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print(f"Exporting model to '{fname_out}'")
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print(f"Exporting model to '{fname_out}'")
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model_instance.write()
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model_instance.write()
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print(f"Model successfully exported to '{fname_out}'")
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print(f"Model successfully exported to '{fname_out}'")
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