Update README.md

README.md

@@ -15,4 +15,26 @@ It uses ChatML/Qwen formatting
 
 This model is trained on a dataset generated by Mistral Small 3, It's goal is to give qwen less robotic and less boring answers.
 
-The dataset is 10k examples from alpaca-cleaned regenerated using owo-speak/uwu-speak
+The dataset is 10k examples from alpaca-cleaned regenerated using owo-speak/uwu-speak
+
+<details>
+<summary>CO2 Emission Related to Experiments</summary>
+
+### CO2 Emission Related to Experiments
+
+Experiments were conducted using a private infrastructure, which has a carbon efficiency of 0.432 kgCO<sub>2</sub>eq/kWh. A cumulative of 1 hours of computation was performed on hardware of type RTX 3090 (TDP of 350W).
+
+Total emissions are estimated to be 0.15 kgCO<sub>2</sub>eq of which 0 percents were directly offset. This is equivalent to 0.61 Km driven by an average ICE car [1].
+
+<!-- Uncomment if you bought additional offsets:
+XX kg CO2eq were manually offset through [Offset Provider](link).
+-->
+
+Estimations were conducted using the [MachineLearning Impact calculator](https://mlco2.github.io/impact#compute) presented in Lacoste et al. (2019).
+
+**References**
+
+*   Lacoste, Alexandre, Alexandra Luccioni, Victor Schmidt, and Thomas Dandres. "Quantifying the Carbon Emissions of Machine Learning." *ArXiv Preprint ArXiv:1910.09700* (2019).
+*   [1] [Greenhouse Gas Equivalencies Calculator - Calculations and References](https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator-calculations-and-references#miles) (Source for ICE car emissions)
+
+</details>