<｜begin▁of▁sentence｜>### Instruction:
Given a fast GNP random graph with 100 nodes and the probability of edge creation p=0.5, can you use Role2Vec model, from the IJCAI '18 paper 'Learning Role-based Graph Embeddings', with specified parameters to get its node embeddings?
### Response:
import networkx as nx
from karateclub import Role2Vec

G = nx.fast_gnp_random_graph(n=100, p=0.5, seed=42)

role2vec = Role2Vec(walk_number=10,
                  walk_length=80,
                  dimensions=128,
                  workers=4,
                  window_size=5,
                  epochs=1,
                  learning_rate=0.05,
                  down_sampling=0.0001,
                  min_count=1,
                  wl_iterations=2,
                  seed=42,
                  erase_base_features=False)

role2vec.fit(G)
embedding = role2vec.get_embedding()

print(embedding)
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