From 0cd637b10aabb85272258c5b3162b54b72a8fa77 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?J=C3=A1n=20Drgo=C5=88a?= Date: Thu, 21 Nov 2024 13:51:57 -0800 Subject: [PATCH] Update README.md --- README.md | 25 ++++++++++++------------- 1 file changed, 12 insertions(+), 13 deletions(-) diff --git a/README.md b/README.md index 6368850f..e67bc2d2 100755 --- a/README.md +++ b/README.md @@ -23,9 +23,9 @@ differentiable models and algorithms embedded with prior knowledge and physics. 1. [Overview](#overview) 2. [Key Features](#key-features) 3. [What's New in v1.5.2](#whats-new) -4. [Getting Started](#getting-started) -5. [Tutorials](#domain-examples) -5. [Installation](#installation) +4. [Installation](#installation) +5. [Getting Started](#getting-started) +6. [Tutorials](#domain-examples) 6. [Documentation and User Guides](#documentation-and-user-guides) @@ -59,19 +59,25 @@ KANs to be trained in parallel to give accurate solutions for multiscale problem > ⭐ [Function Approximation with Kolgomorov-Arnold Networks ](#function-approximation) -## Getting Started + +## Installation +Simply run ``` pip install neuromancer ``` +For manual installation, please refer to [Installation Instructions](INSTALLATION.md) + + +## Getting Started -Extensive set of tutorials can be found in the +An extensive set of tutorials can be found in the [examples](https://github.com/pnnl/neuromancer/tree/master/examples) folder and the [Tutorials](#domain-examples) below. Interactive notebook versions of examples are available on Google Colab! Test out NeuroMANCER functionality before cloning the repository and setting up an environment. -The notebooks below introduce the core abstractions of the NeuroMANCER library, in particular our symbolic programming interface and Node classes. +The notebooks below introduce the core abstractions of the NeuroMANCER library, in particular, our symbolic programming interface and Node classes. ### Symbolic Variables, Nodes, Constraints, Objectives, and Systems Classes @@ -263,13 +269,6 @@ We have integrated PyTorch Lightning to streamline code, enable custom training Open In Colab Part 4: Defining Custom Training Logic via Lightning Modularized Code. -## Installation -Simply run -``` -pip install neuromancer -``` -For manual installation, please refer to [Installation Instructions](INSTALLATION.md) - ## Documentation and User Guides The documentation for the library can be found [online](https://pnnl.github.io/neuromancer/). There is also an [introduction video](https://www.youtube.com/watch?v=YkFKz-DgC98) covering