Update README.md

README.md

@@ -165,25 +165,22 @@ The model was evaluated using a separate test set, comprising 10% of the origina
 <!-- 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). -->
 
 
-\usepackage{hyperref}
-
-\subsection{CO2 Emission Related to Experiments}
 
 Experiments were conducted using a private infrastructure, which has a carbon efficiency of 0.432 kgCO$_2$eq/kWh. A cumulative of 10 hours of computation was performed on hardware of type GTX 1080 (TDP of 180W).
 
-Total emissions are estimated to be 0.78 kgCO$_2$eq of which 0 percents were directly offset.
+Total emissions are estimated to be 0.78 kgCO of which 0 percents were directly offset.
     
-%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}.
+Estimations were conducted using the [MachineLearning Impact calculator](https://mlco2.github.io/impact#compute) presented in presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700)
 
+```
 @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}
 }
+```
                         
 
 - **Hardware Type:** NVIDIA GPUs (GTX 1080)
@@ -214,7 +211,7 @@ The training used PyTorch and the Hugging Face Transformers library, with additi
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
 **BibTeX:**
-
+```
 @misc{phi2functioncalling,
   title={phi-2-function-calling},
   author={Carlos Rodrigues},
@@ -222,6 +219,7 @@ The training used PyTorch and the Hugging Face Transformers library, with additi
   publisher={Hugging Face},
   howpublished={\url{https://huggingface.co/DataKensei/phi-2-function-calling}},
 }
+```
 
 ## Model Card Contact