Teach, test, evaluate language models with MTEB Arena
Display and submit LLM benchmarks
Upload a machine learning model to Hugging Face Hub
Convert Hugging Face models to OpenVINO format
Explore and submit models using the LLM Leaderboard
Open Persian LLM Leaderboard
Browse and evaluate ML tasks in MLIP Arena
Optimize and train foundation models using IBM's FMS
Measure BERT model performance using WASM and WebGPU
Calculate GPU requirements for running LLMs
Display LLM benchmark leaderboard and info
Measure execution times of BERT models using WebGPU and WASM
GIFT-Eval: A Benchmark for General Time Series Forecasting
MTEB Arena is a powerful open-source platform designed for benchmarking and evaluating language models. It provides a comprehensive environment to teach, test, and evaluate AI models, enabling users to assess performance across various tasks and datasets. With MTEB Arena, users can easily create custom benchmarking tasks, run evaluations, and compare results.
Install MTEB Arena:
Configure Your Task:
Run the Benchmark:
Analyze Results:
What is MTEB Arena used for?
MTEB Arena is used for benchmarking and evaluating language models. It allows users to create custom tasks, run evaluations, and analyze results to compare model performance.
Can I use MTEB Arena with any language model?
Yes, MTEB Arena supports a wide range of language models. It is compatible with models from popular libraries like Hugging Face Transformers and other custom models.
How do I install MTEB Arena?
To install MTEB Arena, clone the repository from GitHub or use pip. Follow the installation instructions in the documentation to set up the platform and its dependencies.