<｜begin▁of▁sentence｜>### Instruction:
Given a list of random graphs generated with the GNP model (also known as the Erdős-Rényi model), each with 100 nodes and a probability of 0.05 for edge creation, how can you use the SF model to obtain a fixed-size embedding representing the spectral features of these graphs?
### Response:
import networkx as nx
from karateclub import SF

# Create a list of graphs
G1 = nx.gnp_random_graph(100, 0.05)
G2 = nx.gnp_random_graph(100, 0.05)
graphs = [G1, G2]

# Initialize SF model
model = SF(dimensions=128, seed=42)

# Fit model
model.fit(graphs)

# Get embeddings
embedding = model.get_embedding()
print(embedding)
<|EOT|>
