<｜begin▁of▁sentence｜>### Instruction:
Alright, picture this: you're managing a roster of up-and-coming actors, each with their own unique connections in the industryÃ¢ÂÂthink of it like a sprawling social network. Now, just like when you're trying to land a gig for a client, you don't want to overwhelm the director with your entire lineup. Instead, you need to pick out a select few who really fit the bill. So let's relate this back to our task with a little tech twist.

We've got this intricate web of relationships, like a giant virtual Rolodex in the form of a digital graph, tucked away in a fileÃ¢ÂÂlittleballoffur1.gml for our scene. What we need to do is apply a technique, let's call it the FrontierSampler, it's like our casting tool for graphs. We're aiming to select a subset of these nodes, think of it as our A-listers, for a more intimate networking event.

In the industry talk, we'd say we're sampling a subgraph, but we're not just plucking names out of a hat here. We want control over this list, we want to specify exactly how many of these upstarts we're inviting to our exclusive roundtable. Plus, we want to make sure we've got our top seeds, the influencers who are going to catalyze the conversation, locked in from the get-go.

So, in layman's terms, using the FrontierSampler from this whole littleballoffur setup, how can I pull off this soiree and get a subgraphÃ¢ÂÂthat handpicked VIP list of nodesÃ¢ÂÂfrom our big bash in the littleballoffur1.gml file? And let's not forget, we need to set the number of nodes and make sure our seeds are sown and ready to sprout.
### Response:
import networkx as nx
from littleballoffur import FrontierSampler
G = nx.read_sparse6('littleballoffur1.sparse6')
sampler = FrontierSampler(number_of_seeds=5, number_of_nodes=10)
sampler_G = sampler.sample(G)
print(sampler_G.edges(), sampler_G.nodes());
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