<｜begin▁of▁sentence｜>### Instruction:
Given the Adjacency network of common adjectives and nouns in the novel "David Copperfield" by Charles Dickens, which you can read from a gml file named adjnoun.gml, can you apply both Louvain and Leiden community detection algorithms to find communities of related words and then compute the Normalized F1 score to evaluate the similarity between the two resulting partitions?
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Load a graph of word adjacencies
G = nx.read_gml('adjnoun.gml')

# Apply two community detection algorithms to the graph
louvain_communities = algorithms.louvain(G)
leiden_communities = algorithms.leiden(G)

# Compute the Normalized F1 score between the partitions
nf1_score = evaluation.nf1(louvain_communities, leiden_communities)

# Print the Normalized F1 score
print(nf1_score.score)
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