<｜begin▁of▁sentence｜>### Instruction:
Given a bipartite graph with node set A consisting of nodes ['A', 'B', 'C', 'D'] and node set B consisting of nodes [1, 2, 3, 4]. Edges are [('A', 1), ('B', 1), ('C', 2), ('D', 3), ('A', 4), ('B', 4)]. Can you compute the betweenness centrality for the nodes in this bipartite network using NetworkX, considering the node attribute 'bipartite'?
### Response:
import networkx as nx
from networkx.algorithms import bipartite

# Create a bipartite graph
B = nx.Graph()
B.add_nodes_from(['A', 'B', 'C', 'D'], bipartite=0) # Add the node attribute 'bipartite'
B.add_nodes_from([1, 2, 3, 4], bipartite=1)
B.add_edges_from([('A', 1), ('B', 1), ('C', 2), ('D', 3), ('A', 4), ('B', 4)])

# Separate node sets
top_nodes = set(['A', 'B', 'C', 'D'])

# Compute the betweenness centrality for the nodes in the graph
centrality = bipartite.betweenness_centrality(B, nodes=top_nodes)
print(centrality)
<|EOT|>
