Browse and evaluate ML tasks in MLIP Arena
Optimize and train foundation models using IBM's FMS
Explore GenAI model efficiency on ML.ENERGY leaderboard
Convert Hugging Face models to OpenVINO format
Evaluate adversarial robustness using generative models
Push a ML model to Hugging Face Hub
Quantize a model for faster inference
Display leaderboard for earthquake intent classification models
Evaluate RAG systems with visual analytics
Display model benchmark results
Determine GPU requirements for large language models
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Run benchmarks on prediction models
MLIP Arena is a platform designed for model benchmarking, allowing users to browse and evaluate machine learning models and tasks. It provides a comprehensive environment to explore and compare the performance of different models across various machine learning tasks.
• Task Exploration: Access a wide range of machine learning tasks to analyze model performance.
• Model Comparison: Compare models side-by-side to understand their strengths and weaknesses.
• Performance Visualization: Visualize results and metrics to gain insights into model effectiveness.
• Task Filtering: Narrow down tasks by specific criteria to focus on relevant models.
• Documentation Access: Review detailed documentation for tasks and models to deepen understanding.
What is MLIP Arena used for?
MLIP Arena is used for benchmarking and comparing machine learning models across various tasks, helping users understand model performance and select the best suited for their needs.
Can I filter tasks based on specific criteria?
Yes, MLIP Arena allows users to filter tasks by specific criteria, making it easier to find relevant models and performance data.
Is the performance data subjective?
No, the performance data in MLIP Arena is based on objective metrics and benchmarks, providing unbiased insights into model capabilities.