From 1eaebaef126f632faa271b606a31985d8c868b1b Mon Sep 17 00:00:00 2001 From: Albert Alonso Date: Wed, 8 May 2024 12:52:26 +0200 Subject: [PATCH] docs: simplify readme --- README.md | 19 ------------------- 1 file changed, 19 deletions(-) diff --git a/README.md b/README.md index 6d8905c..8e10b6e 100644 --- a/README.md +++ b/README.md @@ -7,13 +7,6 @@

-[**Installation**](#installation) -| [**Usage**](#usage) -| [**Contributing**](#contributing) -| [**License**](#license) - - - Bayex is a lightweight Bayesian optimization library designed for efficiency and flexibility, leveraging the power of JAX for high-performance numerical computations. This library aims to provide an easy-to-use interface for optimizing expensive-to-evaluate functions through Gaussian Process (GP) models and various acquisition functions. Whether you're maximizing or minimizing your objective function, Bayex offers a simple yet powerful set of tools to guide your search for optimal parameters. @@ -22,18 +15,6 @@ Bayex can be installed using [PyPI](https://pypi.org/project/bayex/) via `pip`: ``` pip install bayex ``` -or from GitHub directly -``` -pip install git+git://github.com/alonfnt/bayex.git -``` - -Likewise, you can clone this repository and install it locally - -```bash -git clone https://github.com/alonfnt/bayex.git -cd bayex -pip install -r requirements.txt -``` ## Usage Using Bayex is quite simple despite its low level approach: