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captum

Open Source
Explainability and Fairness Updated Feb 15, 2026
Compared with 13 other Explainability and Fairness agents Open source Self-hostable Updated Feb 2026
💰 Open Source 🔄 Updated Feb 2026 🖥️ Self-hostable

💰 Pricing

Open Source

Pricing not publicly listed.

🎯 Use Cases

Debugging model predictions by identifying influential input features Validating fairness in AI models by analyzing bias in feature attributions Explaining model decisions to stakeholders for regulatory compliance Improving model performance by understanding misclassifications

⚖️ Pros & Cons

✅ Pros

  • Integrates seamlessly with PyTorch models
  • Supports multiple state-of-the-art interpretability methods
  • Actively maintained by Facebook (Meta) and the open-source community

❌ Cons

  • Limited to PyTorch models (no support for other frameworks)
  • Steep learning curve for users unfamiliar with interpretability techniques
  • May require computational overhead for large models

Overview

Captum is a model interpretability library for PyTorch that provides tools to understand and debug deep learning models. It includes algorithms like integrated gradients, saliency maps, and SmoothGrad to analyze feature importance and model behavior.

Problem It Solves

It helps researchers and developers interpret PyTorch models by revealing how input features influence predictions, improving transparency and trust in AI systems.

Target Audience: Developers and teams working with explainability and fairness automation.

Inputs

  • User configuration
  • API credentials (if required)
  • Task parameters

Outputs

  • Automated task results
  • Status reports
  • Generated content or actions

Example Workflow

  1. 1 User configures the agent with required parameters
  2. 2 Agent receives input data or trigger
  3. 3 Agent processes the request using its core logic
  4. 4 Agent interacts with external services if needed
  5. 5 Results are returned to the user

Sample System Prompt


              You are captum, an AI assistant. Help the user accomplish their task efficiently.

            

Tools & Technologies

LLM APIs Python

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FAQs

Is this agent open-source?
Yes
Can this agent be self-hosted?
Yes
What skill level is required?
Intermediate

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