<｜begin▁of▁sentence｜>### Instruction:
Given a karate_club_graph, can you use the 'MNMF' model from the AAAI '17 paper 'Community Preserving Network Embedding' to model it and obtain both node embeddings and community memberships, with the model's dimensions set to 32, the number of clusters set to 4, and other parameters set at their default values?
### Response:
import networkx as nx
from karateclub import MNMF

# Create a simple graph
G = nx.karate_club_graph()

# Initialize MNMF model with custom parameters
model = MNMF(dimensions=32, clusters=4, lambd=0.2, alpha=0.05, beta=0.05, iterations=100, lower_control=1e-15, eta=5.0, seed=42)

# Fit the model to the graph
model.fit(G)

# Get the embeddings and memberships
embeddings = model.get_embedding()
memberships = model.get_memberships()

# Print the results
print('Embeddings:\n', embeddings)
print('Memberships:\n', memberships)
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