<｜begin▁of▁sentence｜>### Instruction:
Given a random graph generated with 100 nodes and 500 edges, how would you use the Walklets model, as implemented in 'Don’t Walk, Skip! Online Learning of Multi-scale Network Embeddings', to obtain a node embedding?
### Response:
import networkx as nx
from karateclub import Walklets

# Create a random graph
G = nx.gnm_random_graph(100, 500)

# Initialize Walklets instance with parameters
walklets_model = Walklets(walk_number=10, walk_length=80, dimensions=32, workers=4, window_size=4, epochs=1, learning_rate=0.05, min_count=1, seed=42)

# Fit the model
walklets_model.fit(G)

# Get the embedding
embedding = walklets_model.get_embedding()
print(embedding)
<|EOT|>
