jessevig/bertviz

Health v2 · maintenance only

Adoption not part of the score

8160 stars · 885 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

BertViz is an interactive Python library for visualizing attention mechanisms in Transformer language models such as BERT, GPT-2, and RoBERTa. It runs inside Jupyter or Colab notebooks via a simple API supporting most Huggingface models, offering head, model, and neuron views.

Use cases

• visualize attention heads in a BERT model
• understand how transformer layers attend to tokens
• debug why a Huggingface model attends to certain words
• create interactive attention visualizations in a Jupyter notebook
• teach students how self-attention works
• explore query and key neuron interactions in attention computation

When to choose

• you need interactive attention visualizations for Huggingface transformer models
• you work in Jupyter or Colab notebooks
• you want multiple views (head, model, neuron) of attention
• you are teaching or researching transformer interpretability

When to avoid

• you need production model serving or inference
• you use models outside the Huggingface ecosystem
• you need visualizations outside notebook environments
• you want general-purpose neural network visualization beyond attention

Facets

library · maturity stable

data-visualization nlp machine-learning machine-learning data-visualization deep-learning python jvm-scripting transformer-attention bert gpt-2 huggingface jupyter-notebook colab interpretability pytorch natural-language-processing

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