most_downloaeded_model.py

from transformers import Tool
from huggingface_hub import list_models

class HFModelDownloadsTool(Tool):
    name = "model_download_counter"
    description = (
        "This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub. "
        "It takes the name of the category (such as text-classification, depth-estimation, etc), and "
        "returns the name of the checkpoint."
    )

    inputs = ["text"]
    outputs = ["text"]

    def __call__(self, task: str):
        model = next(iter(list_models(filter=task, sort="downloads", direction=-1)))
        return model.id

# Push the tool to the Hub
tool = HFModelDownloadsTool()
tool.push_to_hub("hf-model-downloads")

# Load the tool from the Hub
loaded_tool = Tool.from_hub("hf-model-downloads")

# Instantiate the HfAgent with the additional tool
from transformers import HfAgent

agent = HfAgent("https://api-inference.huggingface.co/models/bigcode/starcoder", additional_tools=[loaded_tool])

# Run the agent with the new tool
result = agent.run(
    "Can you read out loud the name of the model that has the most downloads in the 'text-to-video' task on the Hugging Face Hub?"
)

print(result)