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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): | |
| # Get the current date and date from `days_ago` days ago | |
| today = datetime.utcnow().replace(tzinfo=None) | |
| start_date = (today - timedelta(days=days_ago)).replace(tzinfo=None) | |
| # Initialize an empty list to store the filtered models | |
| recent_models = [] | |
| # Use a generator to fetch models in batches, sorted by likes in descending order | |
| for model in api.list_models(sort="likes", direction=-1): | |
| if model.likes > 10: | |
| if hasattr(model, "created_at") and model.created_at: | |
| # Ensure created_at is offset-naive | |
| created_at_date = model.created_at.replace(tzinfo=None) | |
| if created_at_date >= start_date and model.likes >= min_likes: | |
| 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": model.created_at.strftime("%Y-%m-%d %H:%M"), | |
| "Task": task | |
| }) | |
| else: | |
| # Since the models are sorted by likes in descending order, | |
| # we can stop once we hit a model with 10 or fewer likes | |
| break | |
| # 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.") | |
| with gr.Row(): | |
| likes_slider = gr.Slider(minimum=0, maximum=100, step=10, value=10, label="Minimum Likes") | |
| days_slider = gr.Slider(minimum=1, maximum=7, step=1, value=1, label="Days Ago") | |
| 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], outputs=df) | |
| if __name__ == "__main__": | |
| demo.launch() |