> ## Documentation Index
> Fetch the complete documentation index at: https://docs.trieve.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Working with Reranker

## What is a Reranker / CrossEncoder?

A `Reranker` model provides a powerful semantic boost to the search quality of any keyword or vector search system without requiring overhauls or intensive replacing.

## Using Rerankers with Trieve Vector Inference

<Steps>
  <Step title="Update embedding_models.yaml">
    To use a reranker model with Trieve Vector Inference, you will need to update your embedding\_models.yaml file

    ```yaml embedding_models.yaml theme={null}
    ...
    models:
      ...
      my-reranker-model:
        replicas: 1
        revision: main
        modelName: BAAI/bge-reranker-large
    ...
    ```
  </Step>

  <Step title="Upgrade your TVI cluster">
    Update TVI to include your models

    ```bash theme={null}
    helm upgrade -i vector-inference \
      oci://709825985650.dkr.ecr.us-east-1.amazonaws.com/trieve/trieve-embeddings \
        -f embedding_models.yaml
    ```
  </Step>

  <Step title="Get embeddings endpoint">
    ```sh theme={null}
    kubectl get ing
    ```

    ```
    NAME                                              CLASS   HOSTS   ADDRESS                                                                 PORTS   AGE
    vector-inference-embedding-bge-reranker-ingress   alb     *       k8s-default-vectorin-b09efe8cf6-890425945.us-west-1.elb.amazonaws.com   80      77m
    ```

    The output looks like this
  </Step>
</Steps>