<｜begin▁of▁sentence｜>### Instruction:
Given a GNP random graph with 100 nodes and a 0.05 probability for edge creation, can you use Role2Vec to generate structural node embeddings? Provide the embeddings acquired from the graph using the Role2Vec model with its default parameters.
### Response:
import networkx as nx
from karateclub import Role2Vec

# Create a graph
G = nx.gnp_random_graph(100, 0.05)

# Initialize Role2Vec model
role2vec = Role2Vec(walk_number=10,
                walk_length=80,
                dimensions=128,
                workers=4,
                window_size=2,
                epochs=1,
                learning_rate=0.05,
                down_sampling=0.0001,
                min_count=10,
                wl_iterations=2,
                seed=42,
                erase_base_features=False)

# Fit the model to the graph
role2vec.fit(G)

# Get the embeddings
embeddings = role2vec.get_embedding()

print(embeddings)
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