Guides
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 any overhaul or replacement.
Using Rerankers with Trieve Vector Inference
1
Update embedding_models.yaml
To use a reranker model with Trieve Vector Inference, you will need to update your embedding_models.yaml file
embedding_models.yaml
...
models:
...
my-reranker-model:
replicas: 1
revision: main
modelName: BAAI/bge-reranker-large
...
2
Upgrade your TVF cluster
Update TVF to include your models
helm upgrade -i vector-inference \
oci://registry-1.docker.io/trieve/embeddings-helm \
-f embedding_models.yaml
3
Get embeddings endpoint
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