Finetuning is easy and worthwhile, especially with LoRAs as these Unsloth demos do. The bottleneck then becomes how to self-host the finetuned model in a way that's cost-effective and scalable.
In practice prompt engineering and few-shot prompting with modern LLMs, due to their strong-and-only-getting-better-over-time prompt adherence, tends to be more pragmatic.
In practice prompt engineering and few-shot prompting with modern LLMs, due to their strong-and-only-getting-better-over-time prompt adherence, tends to be more pragmatic.