An overview of prompt engineering techniques for large language models, including zero-shot and few-shot learning methods.
Learn how SetFit, a new approach from Intel Labs and Hugging Face, outperforms GPT-3 for text classification with minimal labeled data.
A guide to implementing few-shot learning using the GPT-Neo language model and Hugging Face's inference API for NLP tasks.
An introduction to meta-learning, a machine learning approach where models learn to adapt quickly to new tasks with minimal data, like 'learning to learn'.
