Update README.md

README.md

@@ -175,11 +175,26 @@ Use the code below to get started with the model.
 
 Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+\usepackage{hyperref}
+
+\subsection{CO2 Emission Related to Experiments}
+
+Experiments were conducted using Google Cloud Platform in region northamerica-northeast1, which has a carbon efficiency of 0.03 kgCO$_2$eq/kWh. A cumulative of 3 hours of computation was performed on hardware of type A100 PCIe 40/80GB (TDP of 250W).
+
+Total emissions are estimated to be 0.02 kgCO$_2$eq of which 100 percents were directly offset by the cloud provider.
+    
+%Uncomment if you bought additional offsets:
+%XX kg CO2eq were manually offset through \href{link}{Offset Provider}.
+
+Estimations were conducted using the \href{https://mlco2.github.io/impact#compute}{MachineLearning Impact calculator} presented in \cite{lacoste2019quantifying}.
+
+@article{lacoste2019quantifying,
+  title={Quantifying the Carbon Emissions of Machine Learning},
+  author={Lacoste, Alexandre and Luccioni, Alexandra and Schmidt, Victor and Dandres, Thomas},
+  journal={arXiv preprint arXiv:1910.09700},
+  year={2019}
+}
+                        
 
 ## Technical Specifications [optional]