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# A simple script that loops over all public models and get their libary_name
import gradio as gr
import pandas as pd
import numpy as np
from collections import Counter
from huggingface_hub import HfApi
from datasets import load_dataset
api = HfApi()
list_models = api.list_models()
def fetch_dataset_and_init():
dataset = load_dataset("librarian-bots/model_cards_with_metadata", split="train")
library_names = dataset["library_name"]
string_counts = Counter(library_names)
string_counts_series = pd.Series(string_counts)
# Sort the series in descending order
df = string_counts_series.sort_values(ascending=False).to_frame()
df.columns = ["count"]
df = df.reset_index()
df_log = df.copy()
df_log['count'] = np.log(df_log['count'])
return df, df_log
df, df_log = fetch_dataset_and_init()
def get_current_nb_models():
# We need this hack since `list_models` returns a generator..
total_models = sum(1 for _ in list_models)
diff_models = total_models - df["count"].sum()
return str(diff_models)
plot_height = 512
plot_width = 1512
top_k = len(df)
def bar_plot_fn(display, top_k):
if display == "simple":
return gr.BarPlot(
df[:top_k],
x="index",
y="count",
tooltip=["index", "count"],
height=plot_height,
width=plot_width
)
elif display == "log":
return gr.BarPlot(
df_log[:top_k],
x="index",
y="count",
tooltip=["index", "count"],
height=plot_height,
width=plot_width
)
with gr.Blocks() as bar_plot:
with gr.Column():
with gr.Column():
display = gr.Dropdown(
choices=[
"simple",
"log",
],
value="simple",
label="Type of Bar Plot",
)
top_k = gr.Slider(
label="Select top-K most used library_name",
value=len(df),
minimum=1,
maximum=len(df),
step=1,
)
with gr.Column():
plot = gr.BarPlot()
with gr.Row():
fetch_button = gr.Button(value="Fetch current number of models without model cards (takes up to 1min to fetch everything)")
text_box = gr.Textbox(value="", label="Number of models without model cards")
top_k.change(bar_plot_fn, inputs=[display, top_k], outputs=plot)
display.change(bar_plot_fn, inputs=[display, top_k], outputs=plot)
fetch_button.click(get_current_nb_models, outputs=[text_box])
bar_plot.load(fn=bar_plot_fn, inputs=[display, top_k], outputs=plot)
bar_plot.launch()