Update README.md

README.md

@@ -134,7 +134,7 @@ We performed automatic evaluation in the style of [Vicuna](https://vicuna.lmsys.
 
 <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
 
-Experiments were conducted using a private infrastructure, which has a carbon efficiency of 0.432 kgCO2eq/kWh. A cumulative of 500 hours of computation was performed on hardware of type Tesla V100-SXM2-32GB (TDP of 300W). Total emissions are estimated to be 64.8 CO2eq of which 0 percents were directly offset. Estimations were conducted using the [MachineLearning Impact calculator](https://mlco2.github.io/impact#compute) presented in [lacoste2019quantifying](https://arxiv.org/abs/1910.09700).
+Experiments were conducted using a private infrastructure, which has a carbon efficiency of 0.432 kgCO2eq/kWh. A cumulative of 500 hours of computation was performed on hardware of type Tesla V100-SXM2-32GB (TDP of 300W). Total emissions are estimated to be 64.8 CO2eq of which 0 percents were directly offset. Estimations were conducted using the [MachineLearning Impact calculator](https://mlco2.github.io/impact#compute).
 
 ## Citation