Update README.md

README.md

@@ -52,7 +52,7 @@ For the XL-Sum task, we choose our best run for each model using the eval set. W
 
 [![Open In Colab][COLAB]](https://colab.research.google.com/github/salrowili/ArabicT5/blob/main/ArabicT5_49GB_Small_on_3070_Laptop_GPU.ipynb)
 
-If you are running your code on a laptop GPU (e.g., a gaming laptop) or limited GPU memory, we recommended using our ArabicT5-49GB-Small model, which was the only model from the list that we were able to run on 3070 Laptop card with a batch size of 8. We manage to achieve an F1 score of 85.391 (slightly better than our FLAX code ) on the TyDi QA task. See the notebook below for reference : 
+If you are running your code on a laptop GPU (e.g., a gaming laptop) or limited GPU memory, we recommended using our ArabicT5-49GB-Small model, which was the only model from the list that we were able to run on 3070 Laptop card with a batch size of 8. We manage to achieve an F1 score of 85.391 (slightly better than our FLAX code ) on the TyDi QA task. 
 
 
 # FineTuning our ArabicT5 model on generative and abstractive tasks with FLAX ###