poppingtonic/transformer-visualization
Mechanistic Interpretability Tutorials, Results and research log as I learn from publicly available research, and experimentation. Evolving work, open ended, slow updates. Lots of incomplete work.
This project helps AI researchers and students understand how large language models like Transformers make decisions. It takes a trained Transformer model and allows you to visualize the internal processing of individual tokens, revealing the 'why' behind its outputs. It also provides pre-generated datasets of specific sentence structures (like Indirect Object Identification) for focused interpretability studies.
No commits in the last 6 months.
Use this if you are a machine learning researcher or student focused on understanding the internal mechanisms of Transformer models, specifically for tasks like token processing and identifying 'induction heads'.
Not ideal if you are looking for a general-purpose model explanation tool for non-Transformer models or production-ready explainable AI (XAI) solutions for end-users.
Stars
9
Forks
3
Language
Jupyter Notebook
License
—
Last pushed
Apr 19, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/poppingtonic/transformer-visualization"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jessevig/bertviz
BertViz: Visualize Attention in Transformer Models
inseq-team/inseq
Interpretability for sequence generation models 🐛 🔍
EleutherAI/knowledge-neurons
A library for finding knowledge neurons in pretrained transformer models.
hila-chefer/Transformer-MM-Explainability
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for...
cdpierse/transformers-interpret
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model...