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A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
| Date | Stars |
|---|---|
| 2026-07-24 | 4022 |
| 2026-07-25 | 4023 |
| 2026-07-28 | 4023 |
| 2026-07-30 | 4023 |
| 2026-08-06 | 4023 |
Today
— stars today
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— stars this month
Momentum
0.0
growth rate 0.00%/day
<p align="center">
<a href="https://github.com/open-spaced-repetition/fsrs4anki/wiki">
<img src="https://github.com/open-spaced-repetition/fsrs4anki/assets/32575846/9efb2ca5-51bd-411d-9694-a77b09f51fa7" width="150" height="150" alt="FSRS4Anki">
</a>
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<div align="center">
# FSRS4Anki
_✨ A modern spaced-repetition scheduler for Anki based on the [Free Spaced Repetition Scheduler algorithm](https://github.com/open-spaced-repetition/awesome-fsrs/wiki/The-Algorithm) ✨_
</div>
<p align="center">
<a href="https://raw.githubusercontent.com/open-spaced-repetition/fsrs4anki/main/LICENSE">
<img src="https://img.shields.io/github/license/open-spaced-repetition/fsrs4anki" alt="license">
</a>
<a href="https://github.com/open-spaced-repetition/fsrs4anki/releases/latest">
<img src="https://img.shields.io/github/v/release/open-spaced-repetition/fsrs4anki?color=blueviolet" alt="release">
</a>
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# Table of contents
- [Introduction](#introduction)
- [How to Get Started?](#how-to-get-started)
- [Add-on Compatibility](#add-on-compatibility)
- [Contribute](#contribute)
- [Contributors](#contributors)
- [Developer Resources](#developer-resources)
- [Stargazers Over Time](#stargazers-over-time)
- [Acknowledgements](#acknowledgements)
# Introduction
FSRS4Anki (Free Spaced Repetition Scheduler for Anki) consists of two main parts: the scheduler and the optimizer.
- The scheduler replaces Anki's built-in scheduler and schedules the cards according to the FSRS algorithm.
- The optimizer uses machine learning to learn your memory patterns and finds parameters that best fit your review history. For details about the working of the optimizer, please read [the mechanism of optimization](https://github.com/open-spaced-repetition/awesome-fsrs/wiki/The-mechanism-of-optimization).
For details about the FSRS algorithm, please read [the algorithm](https://github.com/open-spaced-repetition/awesome-fsrs/wiki/The-Algorithm). If you are interested, you can also read my papers:
- [A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling](https://dl.acm.org/doi/10.1145/3534678.3539081?cid=99660547150) (free access) [[中文版](https://memodocs.maimemo.com/docs/2022_KDD)], and
- [Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory](https://drive.google.com/file/u/0/d/1riJbkH39JB71Wj0AzESTngUM0LaeoD2l/view) (Google Scholar) [[中文版](https://memodocs.maimemo.com/docs/2023_TKDE)].
FSRS Helper is an Anki add-on that complements the FSRS4Anki Scheduler. You can read about it here: https://github.com/open-spaced-repetition/fsrs4anki-helper
# How to Get Started?
If you are using Anki 23.10 or newer, refer to this section of [the Anki manual](https://docs.ankiweb.net/deck-options.html#fsrs).
If you are using an older version of Anki, refer to [this tutorial](https://github.com/open-spaced-repetition/fsrs4anki/blob/main/docs/tutorial2.md).
Note that setting up FSRS is much easier in Anki 23.10 or newer.
# Add-on Compatibility
Some add-ons can cause conflicts with FSRS. As a general rule of thumb, if an add-on affects a card's intervals, it shouldn't be used with FSRS.
| Add-on | Compatible? | Comment |
| ------------------------------------------------------------ |-------------------| ------- |
| [Review Heatmap](https://ankiweb.net/shared/info/1771074083) | Yes :white_check_mark: | Doesn't affect anything FSRS-related. |
| [Advanced Browser](https://ankiweb.net/shared/info/874215009) | Yes :white_check_mark: | Please use the latest version. |
| [Advanced Review Bottom Bar](https://ankiweb.net/shared/info/1136455830) | Yes :white_check_mark: | Please use the latest version. |
| [The KING of Button Add-ons](https://ankiweb.net/shared/info/374005964) | Yes :white_check_mark: | Please use the latest version. |
| [Pass/Fail](https://ankiweb.net/shared/info/876946123) | Yes :white_check_mark: | `Pass` is the equivalent of `Good`, `Fail` is Excerpt of 11,001 characters
Read on GitHub
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Luc Mcgrady · United Kingdom
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Asuka Minato · dify
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John-George Sample · @grafana · United States
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Ikko Eltociear Ashimine · Japan
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:8767ff40871ef390, topic:deep-learning
matched fp:8767ff40871ef390, topic:reinforcement-learning
matched fp:8767ff40871ef390, topic:memory