Text examples

These examples explain machine learning models applied to text data. They are all generated from Jupyter notebooks available on GitHub.

Sentiment analysis

Examples of how to explain predictions from sentiment analysis models.

• Emotion classification multiclass example
• Keras LSTM for IMDB Sentiment Classification
• Positive vs. Negative Sentiment Classification
• Using custom functions and tokenizers

Translation

Examples of how to explain predictions from translation models.

• Machine Translation Explanations

Text generation

Examples of how to explain predictions from text generation models.

• Open Ended GPT2 Text Generation Explanations

Summarization

Examples of how to explain predictions from summarization models.

• Text to Text Explanation: Abstractive Summarization Example

Question Answering

Examples of how to explain predictions from question answering models.

• Explaining a Question Answering Transformers Model

Language modelling

Examples of how to explain predictions from language models.

• Text to Multiclass Explanation: Language Modeling Example

Text entailment

Examples of how to explain predictions from text entailment models.

• Multi-Input Text Explanation: Textual Entailment with Facebook BART