# Explore the power of Pinecone with public collections

> Start your vector-database journey with a click.

Gibbs Cullen · 2022-09-16



![](https://cdn.sanity.io/images/vr8gru94/production/909552c2b5ac2a30d69b35fb5d9916909d793cbb-600x259.png)


**Note: Public collections are no longer supported as part of collections. Visit our [documentation](https://docs.pinecone.io/docs/collections) to learn more. **



Last month, we [announced](https://www.pinecone.io/learn/faster-easier-scalable/) a new feature in public preview: [collections](https://www.pinecone.io/docs/collections/). Collections allow users to save vectors and metadata from an index as a snapshot, and create new indexes from any collection.

Today we are excited to announce the addition of **public collections** to help users quickly run a sample index pre-loaded with data and experience the power of the Pinecone [vector database](https://www.pinecone.io/learn/vector-database/).

## What are public collections?

For users to run a query in Pinecone, they need to upload data to an index. This takes time. Public collections make it easier to explore Pinecone by providing public data from real-world data sources that can be used to create an index in one click.

Pinecone users can now create an index from pre-loaded vector embeddings in one of three example collections. Each collection features data from Pinecone partners:

- Glue SSTB collection from OpenAI
- Text REtrieval Conference (TREC) question classification collection from Cohere
- Stanford Question Answering Dataset (SQuAD) collection from Stanford

These collections contain real-world data, load in less than a minute, and have matching guides to get started:

- [Guide for OpenAI](https://www.pinecone.io/docs/openai/)
- [Guide for Cohere](https://www.pinecone.io/docs/cohere/)
- [Guide for SQuAD](https://www.pinecone.io/docs/examples/extractive-question-answering/)

## How do they work?

The collections are available under **Public Collections** within the [Pinecone console](https://app.pinecone.io/). You can create an index from the example collections and use the [guides](https://www.pinecone.io/docs/collections#public-collections-contain-real-world-data) to get started including code snippets in Python showing how to use the particular index.

![](https://cdn.sanity.io/images/vr8gru94/production/f4b5c8bf7922a6d30700d1fa13698a85a4b9a58c-1000x565.png)


To create an index from a [public collection](https://www.pinecone.io/docs/manage-indexes/#create-an-index-from-a-public-collection), follow these steps:

1. Open the [Pinecone console](https://app.pinecone.com/).
2. Click the name of the project in which you want to create the index.
3. In the left menu, click **Public Collections**.
4. Find the public collection from which you want to create an index. Next to that public collection, click **Create Index**.
5. When index creation is complete, a message appears stating that the index is created and that vectors are successfully upserted. The **Click to View** button will take you to the new index.

![](https://cdn.sanity.io/images/vr8gru94/production/03c47892f7dfada6a77031d78e95d500889dfe8b-1000x565.png)


## Get started today

If you don’t have an embedding model or ready-to-use data to start testing Pinecone, then public collections can help. All Pinecone users will have access to three example collections — Glue SSTB, TREC question classification, and SQuaD — starting today. We will add more public collections over time.

To learn more about public collections, check out the [guides](https://www.pinecone.io/docs/collections#public-collections) or [try them for yourself](https://app.pinecone.io/) in the console.