You can now build a custom text classifier without days of human labeling!
π LLMs work reasonably well as text classifiers. π They are expensive to run at scale and their performance drops in specialized domains.
π Purpose-built classifiers have low latency and can potentially run on CPU. π They require labeled training data.
Combine the best of both worlds: the automatic labeling capabilities of LLMs and the high-quality annotations from human experts to train and deploy a specialized model.
The Synthetic Data Generator now directly integrates with Argilla, so you can generate and curate your own high-quality datasets from pure natural language!
Up next -> include dataset generation for text classification. Other suggestions? Let us know.