<｜begin▁of▁sentence｜>### Instruction:
Given a random graph with 100 nodes and 500 edges, how can the 'Walklets' model be used to compute node embeddings, and what would these embeddings look like?
### Response:
import networkx as nx
from karateclub import Walklets

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

# Instantiate the Walklets model
model = Walklets(walk_number=10, walk_length=80, dimensions=32, workers=4, window_size=5, epochs=1, learning_rate=0.05, min_count=1, seed=42)

# Fit the model
model.fit(G)

# Get the embeddings
embeddings = model.get_embedding()

print(embeddings)
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