docs: add backlinks to ExecuTorch landing page

README.md

@@ -36,7 +36,7 @@
 
 **React Native ExecuTorch** provides a declarative way to run AI models on-device using React Native, powered by **ExecuTorch** :rocket:. It offers out-of-the-box support for a wide range of LLMs, computer vision models, and more. Visit our [HuggingFace](https://huggingface.co/software-mansion) page to explore these models.
 
-**ExecuTorch**, developed by Meta, is a novel framework allowing AI model execution on devices like mobile phones or microcontrollers.
+[**ExecuTorch**](https://executorch.ai), developed by Meta, is a novel framework allowing AI model execution on devices like mobile phones or microcontrollers.
 
 React Native ExecuTorch bridges the gap between React Native and native platform capabilities, enabling developers to efficiently run local AI models on mobile devices. This can be achieved without the need for extensive expertise in native programming or machine learning.
 

docs/docs/01-fundamentals/01-getting-started.md

@@ -22,7 +22,7 @@ import TabItem from '@theme/TabItem';
 
 ## What is ExecuTorch?
 
-ExecuTorch is a novel AI framework developed by Meta, designed to streamline deploying PyTorch models on a variety of devices, including mobile phones and microcontrollers. This framework enables exporting models into standalone binaries, allowing them to run locally without requiring API calls. ExecuTorch achieves state-of-the-art performance through optimizations and delegates such as Core ML and XNNPACK. It provides a seamless export process with robust debugging options, making it easier to resolve issues if they arise.
+[ExecuTorch](https://executorch.ai) is a novel AI framework developed by Meta, designed to streamline deploying PyTorch models on a variety of devices, including mobile phones and microcontrollers. This framework enables exporting models into standalone binaries, allowing them to run locally without requiring API calls. ExecuTorch achieves state-of-the-art performance through optimizations and delegates such as Core ML and XNNPACK. It provides a seamless export process with robust debugging options, making it easier to resolve issues if they arise.
 
 ## React Native ExecuTorch
 

docs/src/components/ReactNativeExecuTorchIntroduction/index.tsx

@@ -6,7 +6,8 @@ const ReactNativeExecuTorchIntroduction = () => {
     <div className={styles.introductionContainer}>
       <h2 className={styles.title}>What is React Native ExecuTorch?</h2>
       <p className={styles.introduction}>
-        React Native ExecuTorch brings Meta’s ExecuTorch AI framework into the
+        React Native ExecuTorch brings Meta’s{' '}
+        <a href="https://executorch.ai">ExecuTorch</a> AI framework into the
         React Native ecosystem, enabling developers to run AI models and LLMs
         locally, directly on mobile devices. It provides a declarative API for
         on-device inference, allowing you to use local AI models without relying

docs/versioned_docs/version-0.6.0/01-fundamentals/01-getting-started.md

@@ -21,7 +21,7 @@ import TabItem from '@theme/TabItem';
 
 ## What is ExecuTorch?
 
-ExecuTorch is a novel AI framework developed by Meta, designed to streamline deploying PyTorch models on a variety of devices, including mobile phones and microcontrollers. This framework enables exporting models into standalone binaries, allowing them to run locally without requiring API calls. ExecuTorch achieves state-of-the-art performance through optimizations and delegates such as Core ML and XNNPACK. It provides a seamless export process with robust debugging options, making it easier to resolve issues if they arise.
+[ExecuTorch](https://executorch.ai) is a novel AI framework developed by Meta, designed to streamline deploying PyTorch models on a variety of devices, including mobile phones and microcontrollers. This framework enables exporting models into standalone binaries, allowing them to run locally without requiring API calls. ExecuTorch achieves state-of-the-art performance through optimizations and delegates such as Core ML and XNNPACK. It provides a seamless export process with robust debugging options, making it easier to resolve issues if they arise.
 
 ## React Native ExecuTorch