<｜begin▁of▁sentence｜>### Instruction:
Given the Les Miserables social graph which you can read from a GML file named lesmis.gml, can you use both the Louvain and Leiden community detection algorithms in cdlib to perform community detection? Then, can you compute the Overlapping Normalized Mutual Information (ONMI) score with the Lancichinetti, Fortunato, and Kertesz (LFK) approach, to assess the similarity between the two resulting community structures?
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Read the Les Miserables graph
G = nx.read_gml('lesmis.gml')

# Detect communities using the Louvain algorithm
louvain_communities = algorithms.louvain(G)

# Detect communities using the Leiden algorithm
leiden_communities = algorithms.leiden(G)

# Evaluate the similarity of the two community partitions using ONMI
onmi = evaluation.overlapping_normalized_mutual_information_LFK(louvain_communities, leiden_communities)

print(onmi.score)
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