Create an Endpoint
After your first login, you will be directed to the Endpoint creation page. As an example, this guide will go through the steps to deploy distilbert-base-uncased-finetuned-sst-2-english for text classification.
1. Enter the Model Database Repository ID and your desired endpoint name:
![select repository](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/1_repository.png)
2. Select your Cloud Provider and region. Initially, only AWS will be available as a Cloud Provider with the us-east-1
and eu-west-1
regions. We will add Azure soon, and if you need to test Endpoints with other Cloud Providers or regions, please let us know.
![select region](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/1_region.png)
3. Define the [Security Level](security) for the Endpoint:
![define security](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/1_security.png)
4. Create your Endpoint by clicking **Create Endpoint**. By default, your Endpoint is created with a medium CPU (2 x 4GB vCPUs with Intel Xeon Ice Lake) The cost estimate assumes the Endpoint will be up for an entire month, and does not take autoscaling into account.
![create endpoint](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/1_create_cost.png)
5. Wait for the Endpoint to build, initialize and run which can take between 1 to 5 minutes.
![overview](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/overview.png)
6. Test your Endpoint in the overview with the Inference widget π π!
![run inference](https://raw.githubusercontent.com/huggingface/hf-endpoints-documentation/main/assets/1_inference.png)