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convert-llama-h5-to-gguf.py : simplify nbytes
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@ -196,17 +196,7 @@ for name in list_vars.keys():
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# if f16 desired, convert any float32 2-dim weight tensors to float16
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data_dtype = np.float16
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nelements = 1
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for i in range(n_dims):
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nelements *= data.shape[n_dims - 1 - i]
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data_nbytes = 0
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if data_dtype == np.float16:
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data_nbytes = nelements * 2
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elif data_dtype == np.float32:
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data_nbytes = nelements * 4
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data_nbytes = data.size * 2 if data_dtype == np.float16 else data.size * 4
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gguf_writer.add_tensor_info(name, data.shape, data_dtype, data_nbytes)
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