API doc: document Paper endpoint

docs/hub/api.md

@@ -17,7 +17,7 @@ Try it out now on our [Playground](https://huggingface.co/spaces/enzostvs/hub-ap
 
 ## Repo listing API
 
-The following endpoints help get information about models, datasets, Spaces, and metrics stored on the Hub.
+The following endpoints help get information about models, datasets, and Spaces stored on the Hub.
 
 <Tip>
 When making API calls to retrieve information about repositories, the <code>createdAt</code> attribute indicates the time when the respective repository was created. It's important to note that there is a unique value, <code>2022-03-02T23:29:04.000Z</code> assigned to all repositories that were created before we began storing creation dates.
@@ -284,6 +284,10 @@ This is equivalent to `huggingface_hub.list_organization_members()`.
 
 The following endpoint gets information about a paper.
 
+### GET /api/papers/{arxiv_id}
+
+Get the API equivalent of the Paper page, i.e., metadata like authors, summary, and discussion comments.
+
 ### GET /api/arxiv/{arxiv_id}/repos
 
 Get all the models, datasets, and Spaces that refer to a paper.

docs/hub/index.md

@@ -91,7 +91,7 @@ We are helping the community work together towards the goal of advancing Machine
 
 The Hugging Face Hub is a platform with over 900k models, 200k datasets, and 300k demos in which people can easily collaborate in their ML workflows. The Hub works as a central place where anyone can share, explore, discover, and experiment with open-source Machine Learning.
 
-No single company, including the Tech Titans, will be able to “solve AI” by themselves – the only way we'll achieve this is by sharing knowledge and resources in a community-centric approach. We are building the largest open-source collection of models, datasets, demos and metrics on the Hugging Face Hub to democratize and advance ML for everyone 🚀.
+No single company, including the Tech Titans, will be able to “solve AI” by themselves – the only way we'll achieve this is by sharing knowledge and resources in a community-centric approach. We are building the largest open-source collection of models, datasets, and demos on the Hugging Face Hub to democratize and advance ML for everyone 🚀.
 
 We encourage you to read the [Code of Conduct](https://huggingface.co/code-of-conduct) and the [Content Guidelines](https://huggingface.co/content-guidelines) to familiarize yourself with the values that we expect our community members to uphold 🤗.
 
@@ -109,7 +109,7 @@ The Hub offers **versioning, commit history, diffs, branches, and over a dozen l
 
 ## Models
 
-You can discover and use dozens of thousands of open-source ML models shared by the community. To promote responsible model usage and development, model repos are equipped with [Model Cards](./model-cards) to inform users of each model's limitations and biases. Additional [metadata](./model-cards#model-card-metadata) about info such as their tasks, languages, and metrics can be included, with training metrics charts even added if the repository contains [TensorBoard traces](./tensorboard). It's also easy to add an [**inference widget**](./models-widgets) to your model, allowing anyone to play with the model directly in the browser! For programmatic access, a serverless API is provided to [**instantly serve your model**](./models-inference).
+You can discover and use dozens of thousands of open-source ML models shared by the community. To promote responsible model usage and development, model repos are equipped with [Model Cards](./model-cards) to inform users of each model's limitations and biases. Additional [metadata](./model-cards#model-card-metadata) about info such as their tasks, languages, and evaluation results can be included, with training metrics charts even added if the repository contains [TensorBoard traces](./tensorboard). It's also easy to add an [**inference widget**](./models-widgets) to your model, allowing anyone to play with the model directly in the browser! For programmatic access, a serverless API is provided to [**instantly serve your model**](./models-inference).
 
 To upload models to the Hub, or download models and integrate them into your work, explore the [**Models documentation**](./models). You can also choose from [**over a dozen libraries**](./models-libraries) such as 🤗 Transformers, Asteroid, and ESPnet that support the Hub.
 

docs/hub/notifications.md

@@ -1,6 +1,6 @@
 # Notifications
 
-Notifications allow you to know when new activities (Pull Requests or discussions) happen on models, datasets, and Spaces belonging to users or organizations you are watching.
+Notifications allow you to know when new activities (**Pull Requests or discussions**) happen on models, datasets, and Spaces belonging to users or organizations you are watching.
 
 By default, you'll receive a notification if:
 
@@ -37,7 +37,7 @@ By default, you'll be watching all the organizations you are a member of and wil
 
 You can also choose to get notified on arbitrary users or organizations. To do so, use the "Watch repos" button on their HF profiles. Note that you can also quickly watch/unwatch users and organizations directly from your [notifications settings](#notifications-settings).
 
-_Unlike Github or similar services, you cannot watch a specific repository. You must watch users/organizations to get notified about any new activity on any of their repositories. The goal is to simplify this functionality for users as much as possible and to make sure you don't miss anything you might be interested in._
+_Unlike GitHub or similar services, you cannot watch a specific repository. You must watch users/organizations to get notified about any new activity on any of their repositories. The goal is to simplify this functionality for users as much as possible and to make sure you don't miss anything you might be interested in._
 
 ## Notifications settings