Spaces:
Sleeping
Sleeping
import os | |
import gradio as gr | |
import pandas as pd | |
import time | |
import threading | |
from huggingface_hub import HfApi | |
from humanize import naturalsize | |
api = HfApi() | |
HF_TOKEN = os.getenv('HF_TOKEN') | |
def clickable(x): | |
return f'<a target="_blank" href="https://huggingface.co/{x}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{x}</a>' | |
def apply_headers(df, headers): | |
tmp = df.copy() | |
tmp.columns = headers | |
return tmp | |
def search(search_text): | |
if not search_text: | |
return df | |
return df[df['👤 Author'].str.contains(search_text, case=False, na=False)] | |
df = pd.read_csv("author_data_hf_merged.csv") | |
df_author_copy = df.copy() | |
df["author"] = df["author"].apply(lambda x: clickable(x)) | |
df['Total Usage'] = df[['models', 'datasets', 'spaces']].sum(axis=1) | |
df = df.sort_values(by='Total Usage', ascending=False) | |
sum_all_author = naturalsize(sum(df['models'].tolist()+df['datasets'].tolist()+df['spaces'].tolist())) | |
naturalsize_columns = ['Total Usage', 'models', 'datasets', 'spaces'] | |
df[naturalsize_columns] = df[naturalsize_columns].map(naturalsize) | |
df['Serial Number'] = [i for i in range(1, len(df)+1)] | |
df = df[['Serial Number', "author", "Total Usage", "models", "datasets", "spaces"]] | |
df = apply_headers(df, ["🔢 Serial Number", "👤 Author", "⚡️ Total Usage", "🏛️ Models", "📊 Datasets", "🚀 Spaces"]) | |
desc = f""" | |
🎯 The Leaderboard aims to track authors data usage in 🤗 Huggingface. | |
## 📄 Information | |
🛠️ This leaderboard consists of 125k authors scraped from [🤗 Huggingface Leaderboard](https://huggingface.co/spaces/Weyaxi/huggingface-leaderboard). | |
These 125k authors have been selected based on their [🤗 Huggingface Leaderboard](https://huggingface.co/spaces/Weyaxi/huggingface-leaderboard) positions: | |
- 🤖 Top 60k authors in the models category | |
- 📊 Top 60k authors in the datasets category | |
- 🚀 Top 50k authors in the spaces category | |
## 📒 Notes | |
Note that these numbers may not be entirely accurate due to the following reasons: | |
- I only calculated the data usage from the main branch and did not include deleted files that cannot be directly seen. | |
- There may be large datasets/models to which I don't have access (either private or gated). | |
# 📶 Total Data Usage From All Authors | |
According to this leaderboard, there is a total of {sum_all_author} of data on this platform. | |
""" | |
# Write note maybe? | |
title = """ | |
<div style="text-align:center"> | |
<h1 id="space-title">💾 Data Leaderboard 💾</h1> | |
</div> | |
""" | |
with gr.Blocks() as demo: | |
gr.Markdown("""<h1 align="center" id="space-title">💾 Data Leaderboard 💾</h1>""") | |
gr.Markdown(desc) | |
with gr.Column(min_width=320): | |
search_bar = gr.Textbox(placeholder="🔍 Search for a author", show_label=False) | |
gr_followers = gr.Dataframe(df, interactive=False, datatype=["number", 'markdown', 'number']) | |
search_bar.submit(fn=search, inputs=search_bar, outputs=gr_followers) | |
demo.launch() |