Interpretable Text Classification: Probing Scikit-LLM Embedding Spaces

A hands-on walkthrough demonstrates how to interpret LLM-generated text embeddings using Scikit-LLM, a probing logistic regression classifier, UMAP visualization, and SHAP values. Using the IMDB movie review dataset and a local Ollama all-minilm model, embeddings are generated for 1,000 reviews, then evaluated for quality via a simple classifier's accuracy metrics, visualized in 2D via UMAP to inspect class separation, and analyzed with SHAP to identify which latent embedding dimensions drive positive versus negative classification predictions.

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