> I was particularly interested in testing models’ ability to reason (i.e., perform a somewhat complex task that requires high context understanding) about out-of-distribution (i.e., unseen) data.
I was under the assumption that finetuneing LLMs was useful only when you need to change the model's tone (speak like a pirate, voldemort etc).
Are there other examples where LLMs were trained to reason a particular way?
I was under the assumption that finetuneing LLMs was useful only when you need to change the model's tone (speak like a pirate, voldemort etc).
Are there other examples where LLMs were trained to reason a particular way?