<｜begin▁of▁sentence｜>### Instruction:
Given a fast_gnp_random_graph with 50 nodes and a probability for edge creation of 0.1, and a random feature matrix with shape (50, 4), how can you use the BANE model to get the node embeddings considering the described parameters in the API doc?
### Response:
import networkx as nx
from karateclub import BANE
import numpy as np

# Step 1: Create a random graph
G = nx.fast_gnp_random_graph(50, 0.1)

# Step 2: Create a random feature matrix
features = np.random.rand(50, 4)

# Step 3: Instantiate BANE model
model = BANE(dimensions=32, svd_iterations=20, seed=42, alpha=0.3, iterations=100, binarization_iterations=20)

# Step 4: Fit the BANE model
model.fit(G, features)

# Step 5: Get the embeddings
embeddings = model.get_embedding()

print(embeddings)
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