# Reranker **`class Reranker`** reranker | **Rerank** first-stage retrieved paragraphs based on the **contextualized similarity** of query <-> paragraph. Pass each **pair of query/paragraph** through a transformer network simultaneously. The **reranker** produces a score indicating the **contextualized similarity** per text pair. Requires a dedicated reranker worker to be registered ([learn more](../../../how-to-guides/how-remote-models.md#search-how-integrate-remote-models)). **`pydantic model PluginConfig`** Fields - `original_score_weight (float)` - `query (str | None)` - `rerank_score_mode (squirro.lib.search.relevancy.plugins.rerank.transformer_rerankers.RerankerScoreMode)` - `reranker_score_weight (float)` - `top_n_items (int)` - `worker (str)` **`PluginConfig.plugin_name: ClassVar[str] = 'reranker'`** Used to register and reference the plugin within a query. **`field PluginConfig.top_n_items: int = 10`** Amount of fetched items that should get reranked **`field PluginConfig.query: Optional[str] = ''`** left side of the text-pair, as used for contexutalized scoring. Per default fetches to supplied searchbar user-terms **`field PluginConfig.worker: str = 'bge'`** What registered reranker worker (@transformer-service) to use. **`field PluginConfig.rerank_score_mode: RerankerScoreMode = RerankerScoreMode.weighted_avg`** How to combine the score from the reranker stage with the original score determined by the retriever. Supported options are weighted_avg (leveraging minmax-normalization) and reranker_only. **`field PluginConfig.reranker_score_weight: float = 0.5`** Weight of the rerank score in the final score calculation. Effectively computing a weighted average of normalized scores if reranker_score_weight + original_score_weight = 1.0 **`field PluginConfig.original_score_weight: float = 0.5`** Weight of the original score in the final score calculation. Effectively computing a weighted average of normalized scores if reranker_score_weight + original_score_weight = 1.0