docs: Update warnings and links in docs (#659)

## Description

- In hooks replaced the links to specific models with links to the
corresponding collections on Hugging Face (related to issue #612)
- Included image segmentation results in the aggregate benchmarks
- Standardized usage of warnings (instead of warnings and cautions) in
both next and 0.5 versions

### Introduces a breaking change?

- [ ] Yes
- [x] No

### Type of change

- [ ] Bug fix (change which fixes an issue)
- [ ] New feature (change which adds functionality)
- [x] Documentation update (improves or adds clarity to existing
documentation)
- [ ] Other (chores, tests, code style improvements etc.)

### Related issues

#612

### Checklist

- [x] I have performed a self-review of my code
- [x] I have commented my code, particularly in hard-to-understand areas
- [x] I have updated the documentation accordingly
- [x] My changes generate no new warnings

---------

Co-authored-by: Anna Szymańska <szymanska.mariaanna@gmail.com>
Co-authored-by: Mateusz Sluszniak <56299341+msluszniak@users.noreply.github.com>
Co-authored-by: Mateusz Słuszniak <mateusz.sluszniak@swmansion.com>

Author: 3 people

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

@@ -76,7 +76,7 @@ If you plan on using your models via require() instead of fetching them from a u
 
 This allows us to use binaries, such as exported models or tokenizers for LLMs.
 
-:::caution
+:::warning
 When using Expo, please note that you need to use a custom development build of your app, not the standard Expo Go app. This is because we rely on native modules, which Expo Go doesn’t support.
 :::
 

docs/docs/02-hooks/01-natural-language-processing/useLLM.md

@@ -197,7 +197,7 @@ Sometimes, you might want to stop the model while it’s generating. To do this,
 
 There are also cases when you need to check if tokens are being generated, such as to conditionally render a stop button. We’ve made this easy with the `isGenerating` property.
 
-:::caution
+:::warning
 If you try to dismount the component using this hook while generation is still going on, it will result in crash.
 You'll need to interrupt the model first and wait until `isGenerating` is set to false.
 :::

docs/docs/02-hooks/01-natural-language-processing/useSpeechToText.md

@@ -20,7 +20,7 @@ description: "Learn how to use speech-to-text models in your React Native applic
 Speech to text is a task that allows to transform spoken language to written text. It is commonly used to implement features such as transcription or voice assistants.
 
 :::warning
-It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-whisper-tiny.en). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/speech-to-text-68d0ec99ed794250491b8bbe). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference

docs/docs/02-hooks/01-natural-language-processing/useTextEmbeddings.md

@@ -17,8 +17,8 @@ description: "Learn how to use text embeddings models in your React Native appli
 
 Text Embedding is the process of converting text into a numerical representation. This representation can be used for various natural language processing tasks, such as semantic search, text classification, and clustering.
 
-:::caution
-It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-all-MiniLM-L6-v2). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/text-embeddings-68d0ed42f8ca0200d0283362). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -141,7 +141,7 @@ For the supported models, the returned embedding vector is normalized, meaning t
 
 ### Inference time
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization.
 :::
 

docs/docs/02-hooks/02-computer-vision/useClassification.md

@@ -8,8 +8,8 @@ Image classification is the process of assigning a label to an image that best d
 Usually, the class with the highest probability is the one that is assigned to an image. However, if there are multiple classes with comparatively high probabilities, this may indicate that the model is not confident in its prediction.
 :::
 
-:::caution
-It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-efficientnet-v2-s). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/classification-68d0ea49b5c7de8a3cae1e68). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -104,7 +104,7 @@ function App() {
 
 ### Inference time
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization.
 :::
 

docs/docs/02-hooks/02-computer-vision/useImageEmbeddings.md

@@ -18,8 +18,8 @@ description: "Learn how to use image embeddings models in your React Native appl
 
 Image Embedding is the process of converting an image into a numerical representation. This representation can be used for tasks, such as classification, clustering and (using contrastive learning like e.g. CLIP model) image search.
 
-:::caution
-It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-clip-vit-base-patch32). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/image-embeddings-68d0eda599a9d37caaaf1ad0). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -119,7 +119,7 @@ For the supported models, the returned embedding vector is normalized, meaning t
 
 ### Inference time
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization. Performance also heavily depends on image size, because resize is expansive operation, especially on low-end devices.
 :::
 

docs/docs/02-hooks/02-computer-vision/useImageSegmentation.md

@@ -4,8 +4,8 @@ title: useImageSegmentation
 
 Semantic image segmentation, akin to image classification, tries to assign the content of the image to one of the predefined classes. However, in case of segmentation this classification is done on a per-pixel basis, so as the result the model provides an image-sized array of scores for each of the classes. You can then use this information to detect objects on a per-pixel basis. React Native ExecuTorch offers a dedicated hook `useImageSegmentation` for this task.
 
-:::caution
-It is recommended to use models provided by us which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-style-transfer-candy), you can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/image-segmentation-68d5291bdf4a30bee0220f4f), you can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -55,7 +55,7 @@ To run the model, you can use the `forward` method. It accepts three arguments:
 - The `classesOfInterest` list contains classes for which to output the full results. By default the list is empty, and only the most probable classes are returned (essentially an arg max for each pixel). Look at [`DeeplabLabel`](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/types/imageSegmentation.ts) enum for possible classes.
 - The `resize` flag says whether the output will be rescaled back to the size of the image you put in. The default is `false`. The model runs inference on a scaled (probably smaller) version of your image (224x224 for `DEEPLAB_V3_RESNET50`). If you choose to resize, the output will be `number[]` of size `width * height` of your original image.
 
-:::caution
+:::warning
 Setting `resize` to true will make `forward` slower.
 :::
 
@@ -98,7 +98,7 @@ function App() {
 
 ### Memory usage
 
-:::warning warning
+:::warning
 Data presented in the following sections is based on inference with non-resized output. When resize is enabled, expect higher memory usage and inference time with higher resolutions.
 :::
 
@@ -108,7 +108,7 @@ Data presented in the following sections is based on inference with non-resized
 
 ### Inference time
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization.
 :::
 

docs/docs/02-hooks/02-computer-vision/useOCR.md

@@ -4,8 +4,8 @@ title: useOCR
 
 Optical character recognition(OCR) is a computer vision technique that detects and recognizes text within the image. It's commonly used to convert different types of documents, such as scanned paper documents, PDF files, or images captured by a digital camera, into editable and searchable data.
 
-:::caution
-It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/software-mansion). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/ocr-68d0eb320ae6d20b5f901ea9). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -292,7 +292,7 @@ You need to make sure the recognizer model you pass in `recognizerSource` matche
 | -------------------------------------------- | -------------------------------------------------- |
 | Original Image                               | Image with detected Text Boxes                     |
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization.
 :::
 

docs/docs/02-hooks/02-computer-vision/useObjectDetection.md

@@ -5,8 +5,8 @@ title: useObjectDetection
 Object detection is a computer vision technique that identifies and locates objects within images or video. It’s commonly used in applications like image recognition, video surveillance or autonomous driving.
 `useObjectDetection` is a hook that allows you to seamlessly integrate object detection into your React Native applications.
 
-:::caution
-It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-ssdlite320-mobilenet-v3-large). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us, which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/object-detection-68d0ea936cd0906843cbba7d). You can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -143,7 +143,7 @@ function App() {
 
 ### Inference time
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization.
 :::
 

docs/docs/02-hooks/02-computer-vision/useStyleTransfer.md

@@ -4,8 +4,8 @@ title: useStyleTransfer
 
 Style transfer is a technique used in computer graphics and machine learning where the visual style of one image is applied to the content of another. This is achieved using algorithms that manipulate data from both images, typically with the aid of a neural network. The result is a new image that combines the artistic elements of one picture with the structural details of another, effectively merging art with traditional imagery. React Native ExecuTorch offers a dedicated hook `useStyleTransfer`, for this task. However before you start you'll need to obtain ExecuTorch-compatible model binary.
 
-:::caution
-It is recommended to use models provided by us which are available at our [Hugging Face repository](https://huggingface.co/software-mansion/react-native-executorch-style-transfer-candy), you can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
+:::warning
+It is recommended to use models provided by us which are available at our [Hugging Face repository](https://huggingface.co/collections/software-mansion/style-transfer-68d0eab2b0767a20e7efeaf5), you can also use [constants](https://github.com/software-mansion/react-native-executorch/blob/main/packages/react-native-executorch/src/constants/modelUrls.ts) shipped with our library.
 :::
 
 ## Reference
@@ -102,7 +102,7 @@ function App() {
 
 ### Inference time
 
-:::warning warning
+:::warning
 Times presented in the tables are measured as consecutive runs of the model. Initial run times may be up to 2x longer due to model loading and initialization.
 :::