<｜begin▁of▁sentence｜>### Instruction:
As a cameraperson, I assist in capturing video footage for various projects, including television programs, documentaries, and news broadcasts. Suppose I have been tasked with creating visual representations of two different graphs with 5 nodes, where the first graph contains 10 edges and the second graph contains 15 edges. To accomplish this, I need to utilize the 'Graph2Vec' model to generate embeddings for the graphs.
### Response:
import networkx as nx
from karateclub import Graph2Vec

# Creating a list of graphs
graphs = [nx.gnm_random_graph(n=5, m=10), nx.gnm_random_graph(n=5, m=15)]

# Initializing Graph2Vec model with specified parameters
model = Graph2Vec(wl_iterations=2, attributed=False, dimensions=128, workers=4,
                 down_sampling=0.0001, epochs=10, learning_rate=0.025,
                 min_count=5, seed=42, erase_base_features=False)

# Fit the model on the graphs
model.fit(graphs)

# Get the embedding of graphs
embedding = model.get_embedding()
print(embedding)
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