<｜begin▁of▁sentence｜>### Instruction:
As a UI designer, you've been tasked with visualizing the High-energy theory collaborations graph obtained from a GML file called "hep-th.gml." Your goal is to create a plot illustrating the distribution of community sizes resulting from the Louvain and Walktrap algorithms. To achieve this, you will need to utilize networkx, a popular Python library for the creation, manipulation, and study of complex networks.
### Response:
from cdlib import algorithms, viz, evaluation
import networkx as nx

# Creating a sample graph from high-energy theory collaborations
G = nx.read_gml('hep-th.gml')

# Applying Louvain method for community detection
communities_louvain = algorithms.louvain(G)

# Applying Walktrap method for community detection
communities_walktrap = algorithms.walktrap(G)

# Plotting the distribution of community sizes
violin_plot = viz.plot_com_stat([communities_louvain, communities_walktrap], evaluation.size)
<|EOT|>
