Model Interpretability for PyTorch
Based on user reviews
Rating Distribution
ml_dev_jonas88
30 days ago
Integrated TCAV in Captum over the past month for my vision-text models. It caught biases I missed before, saving hours of manual checks. Docs are solid, though setup took a bit tweaking with transformers. Honestly, essential for any serious AI dev.
Albert Schaper(Artificial Intelligence, AI Tools)
With a 4.0/5 rating from 1 user review, Captum receives positive evaluation from Albert Schaper for Scientific Research applications. Albert Schaper's knowledge of artificial intelligence highlights the tool's value for scientists needing artificial intelligence solutions.
Pricing: starts at $0 / month(Updated January 2026)
Captum is an open-source library and is free to use.
Usage Model: API Calls — ensuring you only pay for what you actually use.
Captum's free tier enables scientists to experience scientific research capabilities at no cost. The free plan provides essential functionality that's ideal for learning and initial testing. Paid plans expand capabilities significantly, offering advanced features, higher capacity, and dedicated support for scientists with professional scientific research requirements.
Captum is an open-source library for model interpretability and understanding in PyTorch. It provides state-of-the-art algorithms like Integrated Gradients, TCAV, and TracIn, supporting multi-modal models (vision, text, etc.) with minimal modifications.
Understanding the core functionality and approach of Captum.
Captum follows an open-core model—review the code, self-host or use the managed service, and contribute improvements when needed. Community feedback accelerates iteration without sacrificing transparency.
Explore the powerful features that make Captum stand out.
SDKs for Python remove boilerplate and shorten the path to production.
Teams can inspect the codebase and adapt Captum to specific environments.
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Developers use Captum to write code faster, catch bugs early, and refactor legacy systems.
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