sashavor commited on
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248e2bb
1 Parent(s): f924cbe

trying out image

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  1. app.py +9 -9
app.py CHANGED
@@ -54,17 +54,15 @@ electricity = pd.read_csv(electricity_url)
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  servers = pd.read_csv(server_url)
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  embodied_gpu = pd.read_csv(embodied_gpu_url)
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-
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  st.title("AI Carbon Calculator")
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  st.markdown('## Estimate your model\'s CO2 carbon footprint!')
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- st.markdown('Building on the work of the [ML CO2 Calculator](https://mlco2.github.io/impact/), this tool allows you to consider'
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- ' other aspects of your model\'s carbon footprint based on the LCA methodology.')
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-
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- st.markdown('You can use this tool to calculate different aspects of your model: the dynamic emissions, idle emissions embodied emissions.')
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  st.markdown('### Dynamic Emissions')
 
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  with st.expander("Calculate the emissions produced by energy consumption of model training"):
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  col1, col2, col3, col4 = st.columns(4)
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  with col1:
@@ -98,6 +96,8 @@ with st.expander("Calculate the emissions produced by energy consumption of mode
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  st.markdown('### Idle Emissions')
 
 
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  st.markdown('Do you know what the PUE (Power Usage Effectiveness) of your infrastructure is?')
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@@ -107,9 +107,9 @@ st.markdown('Choose your hardware, runtime and cloud provider/physical infrastru
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- st.markdown('#### More information about our Methodology')
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-
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- st.image('images/LCA_CO2.png', caption='The LCA methodology - the parts in green are those we focus on.')
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- modelname = st.selectbox('Choose a model to test', TDP)
 
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  servers = pd.read_csv(server_url)
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  embodied_gpu = pd.read_csv(embodied_gpu_url)
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+ st.image('images/MIT_carbon_image_narrow.png')
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  st.title("AI Carbon Calculator")
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  st.markdown('## Estimate your model\'s CO2 carbon footprint!')
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+ st.markdown('##### You can use this tool to calculate different aspects of your model\'s carbon footprint.')
 
 
 
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  st.markdown('### Dynamic Emissions')
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+ st.markdown('##### These are the emissions produced by generating the electricity needed to train your model.')
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  with st.expander("Calculate the emissions produced by energy consumption of model training"):
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  col1, col2, col3, col4 = st.columns(4)
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  with col1:
 
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  st.markdown('### Idle Emissions')
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+ st.markdown('##### These are the emissions produced by generating the electricity needed to power the rest of the infrastructure'
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+ 'used for model training -- the datacenter, network, heating/cooling, storage, etc.')
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  st.markdown('Do you know what the PUE (Power Usage Effectiveness) of your infrastructure is?')
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+ with st.expander("More information about our Methodology"):
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+ st.markdown('Building on the work of the [ML CO2 Calculator](https://mlco2.github.io/impact/), this tool allows you to consider'
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+ ' other aspects of your model\'s carbon footprint based on the LCA methodology.')
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+ st.image('images/LCA_CO2.png', caption='The LCA methodology - the parts in green are those we focus on.')