<｜begin▁of▁sentence｜>### Instruction:
Imagine you're devising a wellness program aimed at building a community among participants where the connections represent support systems. You want to simulate this network of 100 individuals, conceptualizing each person as a node. The program's design has two main structures for support: a buddy system where each participant is connected to two others with a 50% chance, and a small group system where each participant is connected to three others, also with a 50% chance. This model will help in understanding how relationships might naturally form in the group setting. How could one utilize the 'dual_barabasi_albert_graph' function within the NetworkX toolkit to generate such a randomized graph that mirrors our intended community structure for this wellness program?
### Response:
import networkx as nx

# Parameters for the dual Barabási–Albert model
count_nodes = 100
m1 = 2
m2 = 3
probability_p = 0.5
seed_value = None

# Generate the graph
dual_ba_graph = nx.dual_barabasi_albert_graph(count_nodes, m1, m2, probability_p, seed=seed_value)

# Draw the graph
nx.draw(dual_ba_graph, with_labels=True)
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