<｜begin▁of▁sentence｜>### Instruction:
As a NetworkX expert, I can guide you in embedding the behaviors of your dog group onto a simulated training network. Imagine you have 100 dogs in a park, and each dog has a 10% chance of forming a bond with another. Using a technique similar to DeepWalk model for dogs, we can create relationships among them. Let's deploy the DogWalk API to generate embeddings that mirror these interactions and display the resulting canine social bonds.
### 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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