Models
Using Models Developed by ZeroEntropy
Rerankers
Rerankers are crossencoder neural networks that can boost the accuracy of any search system, you can read more about what rerankers are and when they are most useful in this blog post.
zerank-1 and zerank-1-small
zerank-1
and zerank-1-small
are reranker models developed by ZeroEntropy.
zerank-1
is our flagship state-of-the-art reranker, you can read more about its performance and cost in this blog post.
Both these models can be called, either:
- using the Python and Node SDKs directly,
- within the
top-snippets
endpoints. - using the
models/rerank
API endpoint directly,
zerank-1-small
is under an Apache 2.0 license and is also available through HuggingFace and Baseten.
Will go over each of those methods below with some examples.
Use the ZeroEntropy SDKs
You can use our official Python and Node SDKs to access the models developed by ZeroEntropy.
Here is an example use of the reranker shown below.
Rerank in the queries endpoint
You can pass rerank your initial search results directly within the top-snippets endpoint.
The available models are: zerank-1
and zerank-1-small
.
Below is an example use of the top-snippets
query endpoint within integrated reranking.
Use the ZeroEntropy API
As explained in the API Reference, you can call both rerankers as shown in the example below.