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5 changes: 1 addition & 4 deletions README.md
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Expand Up @@ -26,9 +26,6 @@ Existing forecasting benchmarks usually fall into one of two categories:

`fev` aims for the middle ground - it provides the core benchmarking functionality without introducing unnecessary constraints or bloated dependencies. The library supports point & probabilistic forecasting, different types of covariates, as well as all popular forecasting metrics.

## 📝 Updates
- **2025-09-16**: The new version `0.6.0` contains major new functionality, [updated documentation](https://autogluon.github.io/fev/latest/), as well as some breaking changes to the `Task` API. Please check the [release notes](https://github.com/autogluon/fev/releases) for more details.

## ⚙️ Installation
```
pip install fev
Expand Down Expand Up @@ -123,7 +120,7 @@ fev.leaderboard(summaries)
- [Models](https://autogluon.github.io/fev/latest/tutorials/05-add-your-model/): Evaluate your models and submit results to the leaderboard.
- [API reference](https://autogluon.github.io/fev/latest/api/task/)

Examples of model implementations compatible with `fev` are available in [`examples/`](./examples/).
Model wrappers and instructions for contributing models are available in [`models/`](./models/).


## 🏅 Leaderboards
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# Examples

Model wrappers and instructions for contributing models are now in [`models/`](../models/).

For archival purposes, old wrappers from `examples/` are available on
https://github.com/autogluon/fev/tree/v0.7.0/examples
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