<｜begin▁of▁sentence｜>### Instruction:
Given a GNP random graph with 100 nodes and a probability of 0.05 for edge creation, can you use the LaplacianEigenmaps model with 8 dimensions for embedding and 1000 maximum number of iterations to get its node embeddings?
### Response:
import networkx as nx
from karateclub import LaplacianEigenmaps
import numpy as np
import matplotlib.pyplot as plt

# Step 1: Create a graph
G = nx.gnp_random_graph(100, 0.05, seed=42)

# Step 2: Apply LaplacianEigenmaps model
model = LaplacianEigenmaps(dimensions=8, maximum_number_of_iterations=1000, seed=42)
model.fit(G)

# Step 3: Get the embeddings
embeddings = model.get_embedding()

print(embeddings)
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