Visualize model performance on function calling tasks
Compare and rank LLMs using benchmark scores
Rank machines based on LLaMA 7B v2 benchmark results
Explain GPU usage for model training
Benchmark AI models by comparison
Generate leaderboard comparing DNA models
Browse and submit LLM evaluations
Measure BERT model performance using WASM and WebGPU
View and compare language model evaluations
Convert PyTorch models to waifu2x-ios format
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Push a ML model to Hugging Face Hub
Submit deepfake detection models for evaluation
Nexus Function Calling Leaderboard is a tool designed to visualize and compare the performance of AI models on function calling tasks. It provides a comprehensive platform to evaluate and benchmark models based on their ability to execute function calls accurately and efficiently.
• Real-time Performance Tracking: Monitor model performance in real-time for function calling tasks. • Benchmarking Capabilities: Compare multiple models against predefined benchmarks. • Cross-Model Comparison: Evaluate performance across different models and frameworks. • Task-Specific Filtering: Filter results based on specific function calling tasks or categories. • Data Visualization: Interactive charts and graphs to present performance metrics clearly. • Multi-Data Source Support: Aggregate results from various data sources and platforms. • User-Friendly Interface: Intuitive design for easy navigation and analysis.
What is the purpose of Nexus Function Calling Leaderboard?
The purpose is to provide a standardized platform for comparing the performance of AI models on function calling tasks, enabling developers to make informed decisions.
How often is the leaderboard updated?
The leaderboard is updated in real-time as new models and datasets are added, ensuring the most current performance metrics.
Can I compare custom models on the leaderboard?
Yes, users can upload their custom models to the platform for benchmarking and comparison with existing models.