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Attention Visualization

Visualize and interpret attention patterns in transformer models using tools like BertViz and attention rollout to understand model focus, debug hallucinations, and mitigate bias.

intermediate60 minutes6 steps
The play
  1. Install Required Libraries
    Install `transformers`, `torch`, and `bertviz` using pip.
  2. Load a Pre-trained Transformer Model
    Load a pre-trained BERT model using the `transformers` library.
  3. Prepare Input Text
    Tokenize and prepare the input text for the model.
  4. Get Attention Weights
    Run the model and extract the attention weights.
  5. Visualize Attention with BertViz
    Use BertViz to visualize the attention weights. This requires running a BertViz server. See BertViz documentation for details.
  6. Implement Attention Rollout
    Implement attention rollout to aggregate attention weights across layers.
Starter code
Start by installing the necessary libraries and loading a pre-trained BERT model. Then, tokenize your input text and run it through the model to obtain the attention weights.
Source
Attention Visualization — Action Pack