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import gradio as gr
from huggingface_hub import HfApi
from datetime import datetime, timedelta
import pandas as pd
# Initialize the Hugging Face API
api = HfApi()
def get_recent_models(min_likes, days_ago, filter_string, search_string):
# Calculate the start date for filtering models
start_date = datetime.utcnow() - timedelta(days=days_ago)
# Prepare filter and search substrings
filter_substrings = {sub.strip().lower() for sub in filter_string.split(';') if sub.strip()}
search_substrings = {term.strip().lower() for term in search_string.split(';') if term.strip()}
# Initialize an empty list to store the filtered models
recent_models = []
# Fetch models sorted by likes in descending order
for model in api.list_models(sort="likes", direction=-1):
if model.likes < min_likes:
# Since models are sorted by likes in descending order, break early
break
created_at_date = model.created_at.replace(tzinfo=None) if model.created_at else None
# Ensure the model meets the date, like, search, and filter criteria
if created_at_date and created_at_date >= start_date:
model_id_lower = model.modelId.lower()
if (not search_substrings or any(term in model_id_lower for term in search_substrings)) and \
(not filter_substrings or not any(sub in model_id_lower for sub in filter_substrings)):
task = model.pipeline_tag if hasattr(model, "pipeline_tag") else "N/A"
recent_models.append({
"Model ID": f'<a href="https://huggingface.co/{model.modelId}" target="_blank">{model.modelId}</a>',
"Likes": model.likes,
"Creation Date": created_at_date.strftime("%Y-%m-%d %H:%M"),
"Task": task
})
# Convert the list of dictionaries to a pandas DataFrame
df = pd.DataFrame(recent_models)
return df
# Define the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Model Drops Tracker 🚀")
gr.Markdown(
"Overwhelmed by the rapid pace of model releases? 😅 You're not alone! "
"That's exactly why I built this tool. Easily filter recent models from the Hub "
"by setting a minimum number of likes and the number of days since their release. "
"Click on a model to see its card. Use `;` to split filter and search terms."
)
with gr.Row():
likes_slider = gr.Slider(minimum=1, maximum=100, step=1, value=5, label="Minimum Likes")
days_slider = gr.Slider(minimum=1, maximum=30, step=1, value=3, label="Days Ago")
with gr.Row():
filter_text = gr.Text(label="Filter", max_lines=1, placeholder="Exclude models containing these terms (separate by `;`)")
search_text = gr.Text(label="Search", max_lines=1, placeholder="Include only models containing these terms (separate by `;`)")
btn = gr.Button("Run")
with gr.Column():
df = gr.DataFrame(
headers=["Model ID", "Likes", "Creation Date", "Task"],
wrap=True,
datatype=["html", "number", "str"],
)
btn.click(fn=get_recent_models, inputs=[likes_slider, days_slider, filter_text, search_text], outputs=df)
if __name__ == "__main__":
demo.launch() |