I feel anthropomorphizing is perfectly reasonable especially in this context. How would you like it described?
It's another thing to anthropomorphize by accident or by illusion, as per pareidolia: https://en.wikipedia.org/wiki/Pareidolia . Just as in pareidolia, where the human brain is primed to "see" a human face in a certain pattern of light and shapes, it seems that human brains are primed to "see" a human intelligence in the output of an LLM, because our brains are pattern-matching on "things that look like human speech". But that's a reason to not anthropomorphize LLMs, precisely because people are inclined to do so without thinking.
Terms like “free will” and “intelligence” are too fuzzy to talk about precisely unless we’re on the exact same page regarding what we mean. And applying our imprecise definitions to machines is not doing us any favors.
The neural network training process wants to minimize the neural network's loss function. The neural network, if it "wants" anything, will have such wants as were embedded in its weights through the process of minimize its loss function, which will mostly be "wants" whose satisfactions correlate with reduced loss function. Of course this is using the term "want" in a behaviourally-descriptive sense, not a subjective-experience sense.
For example, AlphaGo's training routine wants to minimize AlphaGo's loss function. AlphaGo wants to beat you at Go.