# Rerank the documents
results = co.rerank(
    model="rerank-v4.0-pro",
    query=query,
    documents=yaml_docs,
    top_n=1,
)
return_results(results, employees)
```

```
Rank: 1
Score: 0.986828
Document: {'name': 'Emma Williams', 'role': 'Product Designer', 'join_date': '2024-06-15', 'email': 'emma@co1t.com', 'status': 'Full-time'}
```

## Multilingual reranking

The Rerank models (`rerank-v4.0-pro`, `rerank-v4.0-fast`, `rerank-v3.5` and `rerank-multilingual-v3.0`) support 100+ languages. This means you can perform semantic search on texts in different languages.

In the example below, we repeat the steps of performing reranking with one difference – changing the model type to a multilingual one. Here, we use the `rerank-v4.0` model. Here, we are reranking the FAQ list using an Arabic query.

```python PYTHON