---
title: ColBERT Reranker
sidebarTitle: "ColBERT"
description: Enhance search results with ColBERT's contextual reranking in LanceDB. Features efficient model deployment, device optimization, and flexible scoring options for vector, FTS, and hybrid search.

---

import { PyRerankingColbertUsage } from '/snippets/integrations.mdx';

# ColBERT Reranker

This reranker uses ColBERT model to rerank the search results. You can use this reranker by passing `ColbertReranker()` to the `rerank()` method. 
> **Note:** Supported query types – Hybrid, Vector, and FTS.


<CodeGroup>
  <CodeBlock filename="Python" language="Python" icon="python">
    {PyRerankingColbertUsage}
  </CodeBlock>
</CodeGroup>

## Accepted Arguments {#accepted-arguments}
| Argument | Type | Default | Description |
| --- | --- | --- | --- |
| `model_name` | `str` | `"colbert-ir/colbertv2.0"` | The name of the reranker model to use.|
| `column` | `str` | `"text"` | The name of the column to use as input to the cross encoder model. |
| `device` | `str` | `None` | The device to use for the cross encoder model. If None, will use "cuda" if available, otherwise "cpu". |
| `return_score` | `str` | `"relevance"` | Options are "relevance" or "all". The type of score to return. If "relevance", will return only the `_relevance_score. If "all" is supported, will return relevance score along with the vector and/or fts scores depending on query type. |


## Supported Scores for each query type {#supported-scores-for-each-query-type}
You can specify the type of scores you want the reranker to return. The following are the supported scores for each query type:

### Hybrid Search {#hybrid-search}
|`return_score`| Status | Description |
| --- | --- | --- |
| `relevance` | ✅ Supported | Results only have the `_relevance_score` column. |
| `all` | ❌ Not Supported | Results have vector(`_distance`) and FTS(`score`) along with Hybrid Search score(`_relevance_score`). |

### Vector Search {#vector-search}
|`return_score`| Status | Description |
| --- | --- | --- |
| `relevance` | ✅ Supported | Results only have the `_relevance_score` column. |
| `all` | ✅ Supported | Results have vector(`_distance`) along with Hybrid Search score(`_relevance_score`). |

### FTS Search {#fts-search}
|`return_score`| Status | Description |
| --- | --- | --- |
| `relevance` | ✅ Supported | Results only have the `_relevance_score` column. |
| `all` | ✅ Supported | Results have FTS(`score`) along with Hybrid Search score(`_relevance_score`). |