<｜begin▁of▁sentence｜>### Instruction:
As a jewelry appraiser, imagine I have been tasked with evaluating and appraising a collection of rare gemstones. Specifically, I need to utilize the GLEE model to generate node embeddings in order to create a comprehensive appraisal report. The gemstone collection represents a network, and I am interested in creating a GLEE instance with the default dimensionality of 128 and a seed value of 42 to fit it to the gemstone network and retrieve the embeddings.
### Response:
import networkx as nx
from karateclub import GLEE
import numpy as np

# Create a sample graph (e.g., the Zachary's karate club graph)
G = nx.karate_club_graph()

# Initialize GLEE model with specified dimensions and random seed
model = GLEE(dimensions=128, seed=42)

# Fit the model using the graph
model.fit(G)

# Get the embedding of nodes in the graph
embedding = model.get_embedding()

# Print or process the embedding
print(embedding)
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