Update README.md

README.md

@@ -9,7 +9,7 @@ pipeline_tag: text-generation
 tags:
 - medical
 ---
-# Model Card for Model ID
+# Model Card for Phi-Med-V1
 
 <!-- Provide a quick summary of what the model is/does. -->
 
@@ -76,6 +76,28 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 - **Cloud Provider:** [Azure]
 - **Compute Region:** [North Europe (Dublin)]
 
+
+\usepackage{hyperref}
+
+\subsection{CO2 Emission Related to Experiments}
+
+Experiments were conducted using Azure in region northeurope, which has a carbon efficiency of 0.62 kgCO$_2$eq/kWh. A cumulative of 100 hours of computation was performed on hardware of type RTX 3090 (TDP of 350W).
+
+Total emissions are estimated to be 21.7 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]