Update README.md

README.md

@@ -11,12 +11,12 @@
 [**Examples**](#examples) |
 [**Contributing**](#contributing)
 
-[![ci](https://github.com/stockeh/mlx-optimizers/workflows/Main/badge.svg?event=push&branch=main)](https://pypi.org/project/mlx-optimizers/)
+[![ci](https://github.com/stockeh/mlx-optimizers/workflows/Main/badge.svg)](https://pypi.org/project/mlx-optimizers/)
 [![PyPI](https://img.shields.io/pypi/v/mlx-optimizers)](https://pypi.org/project/mlx-optimizers/)
 
 A library to experiment with new optimization algorithms in [MLX](https://github.com/ml-explore/mlx). 
 
-- **Diverse Exploration**: includes proven and experimental optimizers like DiffGrad, QHAdam, and Muon (see [docs](https://stockeh.github.io/mlx-optimizers/build/html/optimizers.html)).
+- **Diverse Exploration**: includes proven and experimental optimizers like DiffGrad, QHAdam, and Muon ([docs](https://stockeh.github.io/mlx-optimizers/build/html/optimizers.html)).
 - **Easy Integration**: fully compatible with MLX for straightforward experimentation and downstream adoption.
 - **Benchmark Examples**: enables quick testing on classic optimization and machine learning tasks.
 
@@ -57,4 +57,4 @@ The [examples](examples) folder offers a non-exhaustive set of demonstrative use
 
 Interested in adding a new optimizer? Start with verifying it is not already implemented or in development, then open a new [feature request](https://github.com/stockeh/mlx-optimizers/issues/new?assignees=&labels=&projects=&template=feature_request.md&title=)! If you spot a bug, please open a [bug report](https://github.com/stockeh/mlx-optimizers/issues/new?assignees=&labels=&projects=&template=bug_report.md&title=). 
 
-Developer? See our [contributing](.github/CONTRIBUTING.md) guide.
+Developer? See our [contributing](.github/CONTRIBUTING.md) guide.