Deploying to gh-pages from @ 6411c13 🚀

_sources/index.md

@@ -1,10 +1,10 @@
-Karman Documentation
+AI Benchmarking Tool
 ================================
 
 ![Karman Schematic Illustration](_static/Karman_process_2.png)
 
 
-**karman** is a Python package for data driven thermospheric density estimation with Machine Learning. It offers support for inputs from several different sources (solar proxies, geomagnetic indices, OMNIWeb data, GOES EUV data, SOHO EUV data, POD-derived thermospheric density data and more). It contains models for both nowcasting and forecasting of thermospheric density, leveraging different ML models, including time fusion transformers.
+**Karman** is a Python package for data driven thermospheric density estimation with Machine Learning. It offers support for inputs from several different sources (solar proxies, geomagnetic indices, OMNIWeb data, GOES EUV data, SOHO EUV data, POD-derived thermospheric density data and more). It contains models for both nowcasting and forecasting of thermospheric density, leveraging different ML models, including time fusion transformers.
 
 
 The main developers are [Giacomo Acciarini](https://www.esa.int/gsp/ACT/team/giacomo_acciarini/), [James Walsh](https://walsh.dev/).

index.html

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     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
 
-    <title>Karman Documentation &#8212; karman 2.0 documentation</title>
+    <title>AI Benchmarking Tool &#8212; karman 2.0 documentation</title>
 
 
 
@@ -336,7 +336,7 @@
 
 
 <div id="jb-print-docs-body" class="onlyprint">
-    <h1>Karman Documentation</h1>
+    <h1>AI Benchmarking Tool</h1>
     <!-- Table of contents -->
     <div id="print-main-content">
         <div id="jb-print-toc">
@@ -350,10 +350,10 @@ <h1>Karman Documentation</h1>
 <div id="searchbox"></div>
                 <article class="bd-article">
 
-  <section class="tex2jax_ignore mathjax_ignore" id="karman-documentation">
-<h1>Karman Documentation<a class="headerlink" href="#karman-documentation" title="Link to this heading">#</a></h1>
+  <section class="tex2jax_ignore mathjax_ignore" id="ai-benchmarking-tool">
+<h1>AI Benchmarking Tool<a class="headerlink" href="#ai-benchmarking-tool" title="Link to this heading">#</a></h1>
 <p><img alt="Karman Schematic Illustration" src="_images/Karman_process_2.png" /></p>
-<p><strong>karman</strong> is a Python package for data driven thermospheric density estimation with Machine Learning. It offers support for inputs from several different sources (solar proxies, geomagnetic indices, OMNIWeb data, GOES EUV data, SOHO EUV data, POD-derived thermospheric density data and more). It contains models for both nowcasting and forecasting of thermospheric density, leveraging different ML models, including time fusion transformers.</p>
+<p><strong>Karman</strong> is a Python package for data driven thermospheric density estimation with Machine Learning. It offers support for inputs from several different sources (solar proxies, geomagnetic indices, OMNIWeb data, GOES EUV data, SOHO EUV data, POD-derived thermospheric density data and more). It contains models for both nowcasting and forecasting of thermospheric density, leveraging different ML models, including time fusion transformers.</p>
 <p>The main developers are <a class="reference external" href="https://www.esa.int/gsp/ACT/team/giacomo_acciarini/">Giacomo Acciarini</a>, <a class="reference external" href="https://walsh.dev/">James Walsh</a>.</p>
 <p>Contact info: giacomo.acciarini&#64;gmail.com, james&#64;walsh.dev.</p>
 <div class="toctree-wrapper compound">

install.html

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     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
     <link rel="next" title="Capabilities" href="capabilities.html" />
-    <link rel="prev" title="Karman Documentation" href="index.html" />
+    <link rel="prev" title="AI Benchmarking Tool" href="index.html" />
   <meta name="viewport" content="width=device-width, initial-scale=1"/>
   <meta name="docsearch:language" content="en"/>
   <meta name="docsearch:version" content="" />
@@ -405,7 +405,7 @@ <h2>Getting help<a class="headerlink" href="#getting-help" title="Link to this h
       <i class="fa-solid fa-angle-left"></i>
       <div class="prev-next-info">
         <p class="prev-next-subtitle">previous</p>
-        <p class="prev-next-title">Karman Documentation</p>
+        <p class="prev-next-title">AI Benchmarking Tool</p>
       </div>
     </a>
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objects.inv

@@ -2,4 +2,5 @@
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