<｜begin▁of▁sentence｜>### Instruction:
Given two Erdos-Renyi random graphs with 100 nodes and edge probability of 0.1, how can you use the FeatherGraph model to get their graph-level embeddings?
### Response:
import networkx as nx
from karateclub import FeatherGraph
import numpy as np

# Create NetworkX graphs
G1 = nx.fast_gnp_random_graph(100, 0.1)
G2 = nx.fast_gnp_random_graph(100, 0.1)

# List of graphs
graphs = [G1, G2]

# Initialize FeatherGraph with specified parameters
model = FeatherGraph(order=5, eval_points=25, theta_max=2.5, seed=42, pooling='mean')

# Fit the model
model.fit(graphs)

# Get the embeddings
embeddings = model.get_embedding()

print(embeddings)
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