[FEATURE] Enables /score endpoint for embedding models (#12846)

docs/source/models/pooling_models.md

@@ -108,8 +108,7 @@ A code example can be found here: <gh-file:examples/offline_inference/basic/clas
 ### `LLM.score`
 
 The {class}`~vllm.LLM.score` method outputs similarity scores between sentence pairs.
-It is primarily designed for [cross-encoder models](https://www.sbert.net/examples/applications/cross-encoder/README.html).
-These types of models serve as rerankers between candidate query-document pairs in RAG systems.
+It is designed for embedding models and cross encoder models. Embedding models use cosine similarity, and [cross-encoder models](https://www.sbert.net/examples/applications/cross-encoder/README.html) serve as rerankers between candidate query-document pairs in RAG systems.
 
 :::{note}
 vLLM can only perform the model inference component (e.g. embedding, reranking) of RAG.