<｜begin▁of▁sentence｜>### Instruction:
Can you create an LFR benchmark graph with 250 nodes, a power law exponent for the degree distribution of 3.0, a power law exponent for the community size distribution of 1.5, a fraction of 0.1 for inter-community edges, an average degree of 5, a minimum community size of 20, and a fixed random seed of 10 using NetworkX? Also, can you determine the number of communities and list them?
### Response:
import networkx as nx
from networkx.generators.community import LFR_benchmark_graph

# Parameters for the LFR benchmark graph
n = 250  # Number of nodes
tau1 = 3.0  # Power law exponent for the degree distribution
tau2 = 1.5  # Power law exponent for the community size distribution
mu = 0.1  # Fraction of inter-community edges

# Generate the LFR benchmark graph
G = LFR_benchmark_graph(n, tau1, tau2, mu, average_degree=5, min_community=20, seed=10)

# Retrieve the communities from the node attributes
communities = {frozenset(G.nodes[v]['community']) for v in G}

# Output
print('Number of communities:', len(communities))
print('Communities:', communities)
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