thanks Nima!

app.py

@@ -14,7 +14,7 @@ def write_to_csv(hardware, training_time, provider, carbon_intensity, dynamic_em
         writer = csv.writer(f)
         writer.writerow([hardware, training_time, provider, carbon_intensity, dynamic_emissions])
     api.upload_file(
-        path_or_fileobj="dynamic_emissions.csv",
+        path_or_fileobj=CACHED_FILE_PATH,
         path_in_repo="dynamic_emissions.csv",
         repo_id="sasha/co2_submissions",
         repo_type="dataset",
@@ -62,7 +62,7 @@ st.markdown('## Estimate your model\'s CO2 carbon footprint!')
 st.markdown('Building on the work of the [ML CO2 Calculator](https://mlco2.github.io/impact/), this tool allows you to consider'
             ' other aspects of your model\'s carbon footprint based on the LCA methodology.')
 
-st.markdown('We will consider 3 aspects of your model: the dynamic emissions, idle emissions embodied emissions.')
+st.markdown('You can use this tool to calculate different aspects of your model: the dynamic emissions, idle emissions embodied emissions.')
 
 st.markdown('### Dynamic Emissions')
 with st.expander("Calculate the emissions produced by energy consumption of model training"):