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| from huggingface_hub import HfApi, ModelFilter | |
| from collections import defaultdict | |
| import pandas as pd | |
| import gradio as gr | |
| api = HfApi() | |
| filter = ModelFilter(library="diffusers") | |
| models = api.list_models(filter=filter) | |
| downloads = defaultdict(int) | |
| for model in models: | |
| is_counted = False | |
| for tag in model.tags: | |
| if tag.startswith("diffusers:"): | |
| is_counted = True | |
| downloads[tag[len("diffusers:"):]] += model.downloads | |
| if not is_counted: | |
| downloads["other"] += model.downloads | |
| # Sort the dictionary by keys | |
| sorted_dict = dict(sorted(downloads.items(), key=lambda item: item[1], reverse=True)) | |
| # Convert the sorted dictionary to a DataFrame | |
| df = pd.DataFrame(list(sorted_dict.items()), columns=['Pipeline class', 'Downloads']) | |
| with gr.Blocks() as demo: | |
| gr.DataFrame(df) | |
| demo.launch() | |