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DIME (Dual Interpretable Model-agnostic Explanations) is mainly aimed at Explaining DIET Classifiers in RASA 2.8.X. Models.

Features 🦄

  • Explains RASA DIET Classifiers using feature importance
  • Generates dual feature importance scores (Global FI + Local FI)
  • Efficient
  • Total confidence drop as the feature importance score
  • Able to explain both local and REST Rasa models
  • Easy to use DIME CLI
  • GUI with a dedicated server on-demand
  • Generate, Store, Download, Upload, Peak DIME explanations. Read more on docs
  • Supports Sinhalese unicode / fully Sinhala-English code-switchable

What's Cooking? 🍪

  • DIME for Jupyter Notebooks
  • Stopwords List Generation
  • DIME Example Notebooks
  • DIME for non-DIET text classification models

Limitations and Known Issues 🤏🏽

  • Global Importance is disabled for REST models due to performance bottlenecks
  • Explaining RASA models locally on Notebooks such as CoLab is not supported yet due to dependency issues
  • Benchmark tests are in progress

📒 Docs: https://dime-xai.github.io
📦 PyPi: https://pypi.org/project/dime-xai/1.2.1/
🪵 Full Changelog: https://github.com/DIME-XAI/dime-xai/blob/main/CHANGELOG.md

Release files for dime-xai 1.2.1

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Source distribution for dime-xai 1.2.1
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Table of built distributions (wheels) for dime-xai 1.2.1
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dime_xai-1.2.1-py3-none-any.whl Python 3 none any Details

Total release size: 40.7 MB

Release files / dime_xai-1.2.1.tar.gz

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