<｜begin▁of▁sentence｜>### Instruction:
Given a G(n,p) Erdős-Rényi graph where n=100 and p=0.05, how can the 'LaplacianEigenmaps' model be used to generate a 2-dimensional embedding of the graph?
### Response:
import networkx as nx
from karateclub import LaplacianEigenmaps
import numpy as np
import matplotlib.pyplot as plt

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

# Step 2: Apply Laplacian EigenMaps
model = LaplacianEigenmaps(dimensions=2, seed=42)
model.fit(G)

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