Machine-Learning

Alibi

A Python library for explaining machine learning models.

Status
Not yet determined
Last checked
Checked · Oct 5, 2026
License
Open source
Pricing
Free tier
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What it is

Alibi is an open-source Python library designed to provide algorithms for explaining machine learning models. It focuses on interpretability and explainability, offering tools for counterfactual explanations and other interpretability techniques. Alibi is particularly useful for developers and data scientists who need to understand and trust the decisions made by complex models. Despite its utility, the library has a relatively high number of open issues on GitHub, indicating potential areas for improvement or active development.

Focus on counterfactual explanations for model interpretability.

When it fits — and when it doesn’t

A good fit for

  • Developers needing model interpretability

    Alibi provides tools for understanding complex model decisions.

  • Data scientists working with AI trust issues

    The library's focus on explainability helps build trust in AI systems.

Look elsewhere if

  • Projects requiring frequent updates

    The library has not seen frequent updates recently.

  • Users needing extensive documentation

    Lack of a dedicated homepage or repository link might limit available resources.

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

  1. 01

    High number of open issues

    159 open issues on GitHub

  2. 02

    Limited recent updates

    Last commit was in October 2025

  3. 03

    No official homepage or repository link on npm

    Missing homepage and repository fields in npm data

What it does well

  • High GitHub stars

    2643 stars on GitHub

  • Wide range of explanation techniques

    Supports counterfactual explanations and other interpretability methods

  • Active contributor base

    25 contributors on GitHub

Pricing

Free tier
Yes
Paid from
—
Model
N/A
Enterprise plan
No

Pricing last confirmed Sep 27, 2026.

Performance benchmarks

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Set up Alibi

Setup steps, common gotchas and what to check after 30 days.

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