Update docs around audio and vision

docs/source/_toctree.yml

@@ -2,13 +2,13 @@
   - local: index
     title: 🤗 Datasets
   - local: quickstart
-    title: Quick start
+    title: Quickstart
+  - local: installation
+    title: Installation
   title: Get started
 - sections:
   - local: tutorial
     title: Overview
-  - local: installation
-    title: Installation
   - local: load_hub
     title: Hugging Face Hub
   - local: access

docs/source/installation.md

@@ -1,16 +1,16 @@
 # Installation
 
-Before you start, you will need to setup your environment and install the appropriate packages. 🤗 Datasets is tested on **Python 3.6+**.
+Before you start, you'll need to setup your environment and install the appropriate packages. 🤗 Datasets is tested on **Python 3.6+**.
 
 <Tip>
 
-If you want to use 🤗 Datasets with TensorFlow or PyTorch, you will need to install them separately. Refer to the [TensorFlow](https://www.tensorflow.org/install/pip#tensorflow-2-packages-are-available) or the [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) for the specific install command for your framework.
+If you want to use 🤗 Datasets with TensorFlow or PyTorch, you'll need to install them separately. Refer to the [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2-packages-are-available) or the [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) for the specific install command for your framework.
 
 </Tip>
 
 ## Virtual environment
 
-You should install 🤗 Datasets in a [virtual environment](https://docs.python.org/3/library/venv.html) to keep everything neat and tidy.
+You should install 🤗 Datasets in a [virtual environment](https://docs.python.org/3/library/venv.html) to keep things tidy and avoid dependency conflicts.
 
 1. Create and navigate to your project directory:
 
@@ -19,7 +19,7 @@ You should install 🤗 Datasets in a [virtual environment](https://docs.python.
    cd ~/my-project
    ```
 
-2. Start a virtual environment inside the directory:
+2. Start a virtual environment inside your directory:
 
    ```bash
    python -m venv .env
@@ -35,7 +35,7 @@ You should install 🤗 Datasets in a [virtual environment](https://docs.python.
    source .env/bin/deactivate
    ```
 
-Once you have created your virtual environment, you can install 🤗 Datasets in it.
+Once you've created your virtual environment, you can install 🤗 Datasets in it.
 
 ## pip
 
@@ -51,32 +51,70 @@ Run the following command to check if 🤗 Datasets has been properly installed:
 python -c "from datasets import load_dataset; print(load_dataset('squad', split='train')[0])"
 ```
 
-This should download version 1 of the [Stanford Question Answering Dataset (SQuAD)](https://rajpurkar.github.io/SQuAD-explorer/), load the training split, and print the first training example:
+This command downloads version 1 of the [Stanford Question Answering Dataset (SQuAD)](https://rajpurkar.github.io/SQuAD-explorer/), loads the training split, and prints the first training example. You should see:
 
 ```python
 {'answers': {'answer_start': [515], 'text': ['Saint Bernadette Soubirous']}, 'context': 'Architecturally, the school has a Catholic character. Atop the Main Building\'s gold dome is a golden statue of the Virgin Mary. Immediately in front of the Main Building and facing it, is a copper statue of Christ with arms upraised with the legend "Venite Ad Me Omnes". Next to the Main Building is the Basilica of the Sacred Heart. Immediately behind the basilica is the Grotto, a Marian place of prayer and reflection. It is a replica of the grotto at Lourdes, France where the Virgin Mary reputedly appeared to Saint Bernadette Soubirous in 1858. At the end of the main drive (and in a direct line that connects through 3 statues and the Gold Dome), is a simple, modern stone statue of Mary.', 'id': '5733be284776f41900661182', 'question': 'To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?', 'title': 'University_of_Notre_Dame'}
 ```
 
+## Audio
+
+To work with audio datasets, you need to install the [`Audio`] feature as an extra dependency:
+
+```bash
+pip install datasets[audio]
+```
+
+<Tip warning={true}>
+
+On Linux, non-Python dependency on `libsndfile` package must be installed manually, using your distribution package manager, for example:
+
+```bash
+sudo apt-get install libsndfile1
+```
+
+</Tip>
+
+To support loading audio datasets containing MP3 files, users should also install [torchaudio](https://pytorch.org/audio/stable/index.html) to handle the audio data with high performance:
+
+```bash
+pip install torchaudio
+```
+
+<Tip warning={true}>
+
+torchaudio's `sox_io` [backend](https://pytorch.org/audio/stable/backend.html#) supports decoding MP3 files. Unfortunately, the `sox_io` backend is only available on Linux/macOS and isn't supported by Windows.
+
+</Tip>
+
+## Vision
+
+To work with image datasets, you need to install the [`Image`] feature as an extra dependency:
+
+```bash
+pip install datasets[vision]
+```
+
 ## source
 
-Building 🤗 Datasets from source lets you make changes to the code base. To install from source, clone the repository and install with the following commands:
+Building 🤗 Datasets from source lets you make changes to the code base. To install from the source, clone the repository and install with the following commands:
 
 ```bash
 git clone https://github.com/huggingface/datasets.git
 cd datasets
 pip install -e .
 ```
 
-Again, you can check if 🤗 Datasets has been properly installed with:
+Again, you can check if 🤗 Datasets was properly installed with the following command:
 
 ```bash
 python -c "from datasets import load_dataset; print(load_dataset('squad', split='train')[0])"
 ```
 
 ## conda
 
-🤗 Datasets can also be installed with conda, a package management system:
+🤗 Datasets can also be installed from conda, a package management system:
 
 ```bash
 conda install -c huggingface -c conda-forge datasets
-```
+```