
The author built an end-to-end sentiment analysis pipeline using Scikit-LLM, which integrates large language models directly into scikit-learn workflows. The pipeline processes raw text without requiring traditional feature extraction like TF-IDF or embeddings. This approach simplifies text classification by leveraging LLMs within a familiar scikit-learn interface.
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Summary by ByteBrief
Algorithmic Prompt Refining: Elevating Smaller LLMs with Textual Gradients