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py : fix scalar-tensor conversion [no ci]
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@ -291,8 +291,13 @@ class Model:
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bid = int(part)
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bid = int(part)
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break
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break
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for new_name, data in ((n, d.squeeze().numpy()) for n, d in self.modify_tensors(data_torch, name, bid)):
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for new_name, data_torch in (self.modify_tensors(data_torch, name, bid)):
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data: np.ndarray # type hint
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data = data_torch.squeeze().numpy()
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# if data ends up empty, it means data_torch was a scalar tensor -> restore
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if len(data.shape) == 0:
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data = data_torch.numpy()
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n_dims = len(data.shape)
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n_dims = len(data.shape)
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data_qtype: gguf.GGMLQuantizationType | bool = self.tensor_force_quant(name, new_name, bid, n_dims)
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data_qtype: gguf.GGMLQuantizationType | bool = self.tensor_force_quant(name, new_name, bid, n_dims)
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