| We'll add the not-so-useful yet fun task of fetching the model on the Hugging Face | |
| Hub with the most downloads for a given task. | |
| We can do that with the following code: | |
| thon | |
| from huggingface_hub import list_models | |
| task = "text-classification" | |
| model = next(iter(list_models(filter=task, sort="downloads", direction=-1))) | |
| print(model.id) | |
| For the task text-classification, this returns 'facebook/bart-large-mnli', for translation it returns 'google-t5/t5-base. | |
| How do we convert this to a tool that the agent can leverage? All tools depend on the superclass Tool that holds the | |
| main attributes necessary. |