csinva/imodelsX
Interpret text data with LLMs (sklearn compatible).
This project helps scientists, marketers, or data analysts understand why a large language model (LLM) makes certain predictions on text data. You input text and an LLM's output, and it provides natural language explanations or prompts that clarify the LLM's behavior or patterns in the data. This is useful for anyone needing to interpret or guide an LLM's decisions.
175 stars. Available on PyPI.
Use this if you need clear, human-readable explanations for how an LLM processes text, predicts outcomes, or differentiates between text distributions.
Not ideal if you are looking for a simple, off-the-shelf text generation tool without the need for deep interpretability or steering capabilities.
Stars
175
Forks
28
Language
Python
License
MIT
Last pushed
Jan 27, 2026
Commits (30d)
0
Dependencies
13
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