README.md

metadata

title: best-model-search
app_file: main.py
sdk: gradio
sdk_version: 5.23.1

Model Recommender

An intelligent agent that searches for and recommends the best AI models for specific tasks by analyzing leaderboards, benchmarks, and arenas across the Hugging Face ecosystem. This tool represents the first step towards self-assembling and self-improving AI systems.

Overview

The Model Recommender automates the process of finding optimal AI models for specific tasks by searching through Hugging Face's extensive collection of leaderboards, benchmarks, and model arenas. Instead of manually comparing models across different evaluation metrics, this agent can quickly identify the top-performing models for your specific use case, saving valuable research time and ensuring you're using state-of-the-art solutions.

How It Works

This tool leverages the Hugging Face API to search for and analyze model benchmarking spaces. When given a task description, the agent:

1. Searches for relevant leaderboards, benchmarks, and arenas using targeted queries
2. Analyzes the search results to identify the most relevant evaluation spaces
3. Examines the content of these spaces to extract model performance data
4. Compiles a ranked list of the best models for the specified task
5. Provides detailed information about each model, including performance metrics and links

The agent can also download and examine specific files from Hugging Face Spaces to extract more detailed information about model performance and implementation details.

Features

• Intelligent Leaderboard Search: Finds relevant model evaluation spaces based on task descriptions
• Comprehensive Model Analysis: Examines multiple evaluation metrics to identify truly optimal models
• Detailed Reporting: Provides performance metrics, model links, and implementation details
• Space Content Examination: Can inspect the contents of Hugging Face Spaces to extract additional information
• File Download Capability: Can download specific files or entire repositories for deeper analysis

Installation

Install the required dependencies:

pip install -r requirements.txt

Usage

Run the application:

python main.py

This will launch a Gradio interface where you can:

1. Enter a task description (e.g., "text classification", "image generation", "question answering")
2. The agent will search for relevant leaderboards and benchmarks
3. Review the recommended models, their performance metrics, and links to learn more

Example Queries

• "Find the best models for text classification"
• "What are the top performing models for image generation?"
• "I need a model for question answering in a production environment"
• "Which models perform best on the GLUE benchmark?"

Towards Self-Assembling AI Systems

This Model Recommender represents the first step towards truly self-assembling and self-improving AI systems. By automating the discovery and evaluation of model components, we're building the foundation for systems that can:

1. Self-Optimize: Automatically identify and integrate better-performing components
2. Self-Assemble: Combine specialized models to solve complex tasks
3. Self-Evaluate: Understand their own performance characteristics and limitations

Future iterations will expand beyond model discovery to include automated fine-tuning, integration, and deployment - moving us closer to AI systems that can improve themselves with minimal human intervention.

Customization

To modify the search behavior or add additional tools, edit the main.py file:

• Adjust the search_words list in the leaderboard_search function to target different types of evaluation spaces
• Add new tools to extract more specific information from Hugging Face repositories
• Modify the agent description to focus on specific types of models or evaluation metrics