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SetFit is an efficient and prompt-free framework for few-shot fine-tuning of Sentence Transformers. It achieves high accuracy with little labeled data - for instance, with only 8 labeled examples per class on the Customer Reviews sentiment dataset, SetFit is competitive with fine-tuning RoBERTa Large on the full training set of 3k examples.
Features
- Few-shot learning for text classification
- Optimized for efficiency with minimal labeled data
- Uses contrastive learning for improved performance
- Compatible with Hugging Face Transformers
- Works with various sentence embedding models
- Supports rapid fine-tuning and inference
Project Samples
License
Apache License V2.0Follow SetFit
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