Update README.md

README.md

@@ -121,7 +121,7 @@ We evaluated quantized models in various tasks against the original model.
 Specifically, we evaluated all models using the reading comprehension multiple-choice 
 question-answering benchmark of [<span style="font-variant:small-caps;">Belebele</span>](https://github.com/facebookresearch/belebele) (Persian subset) and reported the accuracy of each model. 
 Additionally, we evaluated our models for Persian-to-English and English-to-Persian translation tasks. 
-For this, we utilized the Persian-English subset of the [Flores-200](https://github.com/facebookresearch/flores/tree/main/flores200) dataset and
+For this, we utilized the Persian-English subset of the [<span style="font-variant:small-caps;">Flores</span>-200](https://github.com/facebookresearch/flores/tree/main/flores200) dataset and
 reported our results using the <span style="font-variant:small-caps;">Comet</span> metric. 
 Furthermore, we calculated the average number of generated tokens per second by each model during running the translation tasks. 
 To understand resource efficiency, we measured the memory usage of each model by employing the `get_memory_footprint()` function.