<｜begin▁of▁sentence｜>### Instruction:
As a web developer, when working on a project involving social network analysis, you may encounter the need to use the Spectral Features model to obtain embeddings for two random G(n,p) graphs with `n=10` nodes and `p=0.5` probability of edge creation. This process can help in analyzing and visualizing the structure and connections within the networks, leading to better insights and improvements for your web applications.
### Response:
import networkx as nx
from karateclub import SF

# Step 1: Create sample networkx graphs
G1 = nx.gnp_random_graph(10, 0.5, seed=42)
G2 = nx.gnp_random_graph(10, 0.5, seed=24)
graphs = [G1, G2]

# Step 2: Apply the SF (Spectral Features) model
sf_model = SF(dimensions=128, seed=42)
sf_model.fit(graphs)

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

print(embeddings)
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