Fine-Tuning vs Prompting for Intent Classification: A Concrete Comparison
We had 8,000 labeled support intents. I ran the same task through GPT-4o prompting and a fine-tuned distilbert. The answer isn't what the blog posts say.
We had 8,000 labeled support intents. I ran the same task through GPT-4o prompting and a fine-tuned distilbert. The answer isn't what the blog posts say.
A Reddit user's LoRA fine-tune on a Qwen model shows how a targeted dataset can produce more 'humanlike' chat than a generic model.