<｜begin▁of▁sentence｜>### Instruction:
Given a random GNP graph with 100 nodes and a probability of edge creation of 0.1, can you use the DeepWalk model to create embeddings for the graph's nodes? You should generate embeddings using the provided parameters and print the resulting embeddings.
### Response:
import networkx as nx
from karateclub import DeepWalk

# Create a graph
G = nx.gnp_random_graph(100, 0.1)

# Initialize DeepWalk using the desired parameters
model = DeepWalk(walk_number=10,
                walk_length=80,
                dimensions=128,
                workers=4,
                window_size=5,
                epochs=3,
                learning_rate=0.05,
                min_count=1,
                seed=42)

# Fit the model on the graph
model.fit(G)

# Retrieve the node embeddings
embeddings = model.get_embedding()

# Perform any downstream task with the embeddings (e.g., visualization, clustering)
print(embeddings)
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