Corey Morris commited on
Commit
b601bef
1 Parent(s): 383dc16
Files changed (1) hide show
  1. app.py +0 -4
app.py CHANGED
@@ -1,7 +1,6 @@
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  import streamlit as st
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  import pandas as pd
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  import plotly.express as px
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- from result_data_processor import ResultDataProcessor
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  import matplotlib.pyplot as plt
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  import numpy as np
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  import plotly.graph_objects as go
@@ -111,8 +110,6 @@ def find_top_differences_table(df, target_model, closest_models, num_differences
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  unique_top_differences_tasks = list(set(top_differences_table['Task'].tolist()))
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  return top_differences_table, unique_top_differences_tasks
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- # data_provider = ResultDataProcessor()
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-
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  # st.title('Model Evaluation Results including MMLU by task')
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  st.title('Interactive Portal for Analyzing Open Source Large Language Models')
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  st.markdown("""***Last updated September 30th***""")
@@ -135,7 +132,6 @@ data_df.set_index("Model Name", inplace=True)
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  filters = st.checkbox('Select Models and/or Evaluations')
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  # Initialize selected columns with "Parameters" and "MMLU_average" if filters are checked
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- # selected_columns = ['Parameters', 'MMLU_average'] if filters else data_provider.data.columns.tolist()
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  selected_columns = ['Parameters', 'MMLU_average'] if filters else data_df.columns.tolist()
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  # Initialize selected models as empty if filters are checked
 
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  import streamlit as st
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  import pandas as pd
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  import plotly.express as px
 
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  import matplotlib.pyplot as plt
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  import numpy as np
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  import plotly.graph_objects as go
 
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  unique_top_differences_tasks = list(set(top_differences_table['Task'].tolist()))
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  return top_differences_table, unique_top_differences_tasks
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  # st.title('Model Evaluation Results including MMLU by task')
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  st.title('Interactive Portal for Analyzing Open Source Large Language Models')
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  st.markdown("""***Last updated September 30th***""")
 
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  filters = st.checkbox('Select Models and/or Evaluations')
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  # Initialize selected columns with "Parameters" and "MMLU_average" if filters are checked
 
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  selected_columns = ['Parameters', 'MMLU_average'] if filters else data_df.columns.tolist()
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  # Initialize selected models as empty if filters are checked