From 6b680940fcfb5a7ad6d052fd6e6134c8b64119fa Mon Sep 17 00:00:00 2001 From: TilliFe Date: Thu, 18 Jul 2024 15:57:18 +0200 Subject: [PATCH] update readme --- README.md | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index f845ef6..2ae908d 100644 --- a/README.md +++ b/README.md @@ -13,18 +13,17 @@
- [Website] | [Docs] | [Getting Started] | [Our Mission] + [Website] | [Docs] | [Getting Started] - [Website]: https://endia.org - [Docs]: https://endia.org - [Getting Started]: #getting-started - [Our Mission]: #our-mission + [Website]: https://endia.vercel.app/ + [Docs]: https://endia.vercel.app/docs/array + [Getting Started]: https://endia.vercel.app/docs/get_started
## Installation -1. **Install [Mojo and MAX](https://docs.modular.com/max/install)** 🔥 (v24.4) +1. **Install [Mojo and MAX](https://docs.modular.com/max/install)** 🔥 (v24.4.0) 2. **Clone the repository**: @@ -42,7 +41,7 @@ Required dependencies: `torch`, `numpy`, `graphviz`. These will be installed automatically by the setup script. -## Getting Started +## A tiny example In this guide, we'll demonstrate how to compute the **value**, **gradient**, and the **Hessian** (i.e. the second-order derivative) of a simple function. First by using Endia's Pytorch-like API and then by using a more Jax-like functional API. In both examples, we initially define a function **foo** that takes an array and returns the sum of the squares of its elements.