> ## Documentation Index
> Fetch the complete documentation index at: https://fpde-80-mintlify-48090872.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Week of June 1, 2026

> FPDE v0.1.0 ships on PyPI with prototype-contrast attribution, validation helpers, and MIT or Apache-2.0 dual licensing.

## New features

**FPDE is on PyPI.** The first public release (`v0.1.0`) of the `fpde` package is available.
Install it with `python -m pip install fpde`.
See the [quickstart](/quickstart) to run your first explanation.

**Prototype-contrast explanations.** FPDE builds class-mean prototypes from training data and explains target-versus-rival evidence with Diff-FPDE, Cos-FPDE, and Hyb-FPDE.

**Validation helpers.** Use `FPDEEngine.select_lambda` to choose `lambda_hyb` on held-out validation data.
Use `perturbation_curves` to compute deletion and insertion curves for an attribution vector.

## Updates

**Dual license.** The package is distributed under `MIT OR Apache-2.0`.
You may choose either license.

**Continuous publishing.** Releases flow through automated publishing to PyPI.