<｜begin▁of▁sentence｜>### Instruction:
As a museum curator, imagine you have been tasked with managing a collection of artifacts from different historical eras. You have a digital representation of the artifacts' connections stored in a GML file named hep-th.gml. How would you employ the head/tail breaks community detection algorithm available in the cdlib API to identify distinct groupings of artifacts, enabling you to better understand the relationships and interactions between them?
### Response:
from cdlib import algorithms
import networkx as nx

# Create a graph from the High-energy theory collaborations dataset
g = nx.read_gml('hep-th.gml')

# Apply the head/tail breaks community detection algorithm
communities = algorithms.head_tail(g, head_tail_ratio=0.8)

# Output the detected communities
for community in communities.communities:
    print(community)
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