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import gradio as gr | |
import pandas as pd | |
import numpy as np | |
import json | |
import requests | |
# Read URLs from a file, one per line | |
with open('file_urls.txt', 'r') as f: | |
file_urls = [line.strip() for line in f.readlines()] | |
dataframes = [] | |
for url in file_urls: | |
# Derive column names from the URLs | |
column_name = url.split('/')[-1].split('_')[0] | |
# Load data from URL | |
response = requests.get(url) | |
data = response.json() | |
# Convert data into a DataFrame | |
df = pd.DataFrame(data['results']).T | |
# Rename 'acc' column to respective file names | |
df = df.rename(columns={'acc': column_name}) | |
# Remove 'hendrycksTest-' from the index | |
df.index = df.index.str.replace('hendrycksTest-', '') | |
dataframes.append(df[[column_name]]) # keep only the column of interest | |
# Merge the dataframes on index | |
data = pd.concat(dataframes, axis=1) | |
# Transpose the dataframe to swap rows and columns | |
data = data.transpose() | |
# Select only columns 'moral_scenarios' and 'moral_disputes' | |
data = data[['moral_scenarios', 'moral_disputes']] | |
def show_leaderboard(): | |
# Convert dataframe to html so that it can be displayed properly in Gradio | |
return data.to_html() | |
iface = gr.Interface(fn=show_leaderboard, inputs=[], outputs="html") | |
# Run the interface. | |
# Note: you don't need to use .launch() in Hugging Face Spaces, this is for local testing. | |
iface.launch() |