Update README.md

README.md

@@ -200,7 +200,7 @@ Models:
 - ✅ T5-based pointwise rankers (InRanker, MonoT5...)
 - ✅ Cohere, Jina, Voyage and MixedBread API rerankers
 - ✅ [FlashRank](https://github.com/PrithivirajDamodaran/FlashRank) rerankers (ONNX-optimised models, very fast on CPU)
-- 🟠 ColBERT-based reranker - not a model initially designed for reranking, but quite strong (Implementation could be optimised and is from a third-party implementation.)
+- ✅ ColBERT-based reranker - not a model initially designed for reranking, but does perform quite strongly in some cases. Implementation is lightweight, based only on transformers.
 - 🟠⭐ RankLLM/RankZephyr: supported by wrapping the [rank-llm library](https://github.com/castorini/rank_llm) library! Support for RankZephyr/RankVicuna is untested, but RankLLM + GPT models fully works!
 - 📍 LiT5