Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
Understand how your AI models make decisions with just two lines of code for explanations.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeModel explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
transformers-interpret has 1.4k stars on GitHub. It has been forked 100 times. transformers-interpret is written mainly in Jupyter Notebook. It has been in active development since 2020. transformers-interpret is available under the Apache-2.0 license. Its main topics are captum, computer-vision, deep-learning, explainable-ai.
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
transformers-interpret is an open-source project. It is released under the Apache-2.0 license.
Yes. transformers-interpret is free and open source — you can use, modify and self-host it.
transformers-interpret is available under the Apache-2.0 license.
transformers-interpret is written mainly in Jupyter Notebook.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/cdpierse-transformers-interpret.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.