Browse and evaluate ML tasks in MLIP Arena
Create and manage ML pipelines with ZenML Dashboard
Find recent high-liked Hugging Face models
Quantize a model for faster inference
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
Calculate memory usage for LLM models
Create and upload a Hugging Face model card
Optimize and train foundation models using IBM's FMS
Measure BERT model performance using WASM and WebGPU
Explore and visualize diverse models
Track, rank and evaluate open LLMs and chatbots
View and submit LLM benchmark evaluations
Evaluate code generation with diverse feedback types
MLIP Arena is a platform designed for model benchmarking, enabling users to browse and evaluate machine learning models across various tasks. It serves as a centralized hub for exploring and comparing the performance of different models, providing valuable insights for both researchers and practitioners.
• Model Library: Access a comprehensive library of pre-trained machine learning models. • Performance Comparison: Compare models across multiple metrics and benchmarks. • Task-Specific Analysis: Evaluate models based on specific tasks such as classification, regression, etc. • Customizable Benchmarks: Define custom evaluation criteria tailored to your needs. • Visualizations: Interactive charts and graphs to simplify performance analysis. • Cross-Model Insights: Identify strengths and weaknesses of different models. • Integration Support: Connect with popular machine learning frameworks and platforms.
What is MLIP Arena used for?
MLIP Arena is used for benchmarking and evaluating machine learning models across various tasks and datasets. It helps users compare model performance and identify the best-suited models for their use cases.
Do I need to register to use MLIP Arena?
No, while some features may require an account, basic browsing and evaluation of models are typically available without registration.
Can I evaluate custom models in MLIP Arena?
Yes, MLIP Arena supports the evaluation of custom models. You can upload your models and benchmark them against existing ones in the library.