<｜begin▁of▁sentence｜>### Instruction:
Imagine you're overseeing an exhibition that showcases two different collections of artifacts, each labeled and classified by different teams of experts. Suppose we have two lists: one is the definitive catalog of artifacts ('y_true'), annotated meticulously by your museum's leading curator, and the other ('y_pred') is a preliminary classification made by an external institution. In preparation for a grand exhibition, we wish to harmonize these two catalogs, ensuring that the external classification aligns perfectly with our museum's own system. 

To achieve this, we'd look to employ the 'remap_labels' function from the graspologic.utils API. Could you suggest how we might utilize this tool to reorder the labels in the 'y_pred' array to correspond seamlessly with the 'y_true' array, and in the process of doing so, record the transformation of labels in a dictionary format? This would greatly assist in maintaining a consistent narrative and coherent storytelling for our visitors.
### Response:
import numpy as np
from graspologic.utils import remap_labels

y_true = np.array([0, 0, 1, 1, 2, 2])
y_pred = np.array([2, 2, 1, 1, 0, 0])

remapped_y_pred, label_map = remap_labels(y_true, y_pred, return_map=True)

print('Remapped labels:', remapped_y_pred)
print('Label mapping:', label_map)
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