<｜begin▁of▁sentence｜>### Instruction:
Given a list of 10 random graphs (G(n,p) model) with 100 nodes and probability 0.5 for edge creation, how can you use the FeatherGraph model from the CIKM '20 paper 'Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models' to get their embeddings?
### Response:
import networkx as nx
from karateclub import FeatherGraph

# Create a list of random graphs
graphs = [nx.gnp_random_graph(100, 0.5, seed=i) for i in range(10)]

# Instantiate the FeatherGraph model with default parameters
model = FeatherGraph()

# Fit the model
model.fit(graphs)

# Get the embeddings
embeddings = model.get_embedding()

print(embeddings)
<|EOT|>
