Hugging Face has introduced SetFit, a novel few-shot learning approach that achieves state-of-the-art performance without requiring prompt engineering. This method utilizes a two-stage process: first, it fine-tunes a model on a small set of labeled data, and then it generates synthetic data from this fine-tuned model to further train it. SetFit has demonstrated impressive results, outperforming prompt-based methods like few-shot GPT-3 on several benchmarks, and is available as an open-source library. AI
Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →
RANK_REASON Open-source library release and paper detailing a new few-shot learning method.