Analyze model errors with interactive pages
Track, rank and evaluate open LLMs and chatbots
Display genomic embedding leaderboard
Measure BERT model performance using WASM and WebGPU
Display leaderboard of language model evaluations
Measure execution times of BERT models using WebGPU and WASM
View and submit LLM benchmark evaluations
Calculate survival probability based on passenger details
View and submit language model evaluations
Generate leaderboard comparing DNA models
Search for model performance across languages and benchmarks
Rank machines based on LLaMA 7B v2 benchmark results
View and submit LLM benchmark evaluations
ExplaiNER is a cutting-edge tool designed for model benchmarking and error analysis. It provides an interactive environment to help users identify and understand model errors through detailed, user-friendly pages. Whether you're refining your model's performance or comparing different AI solutions, ExplaiNER offers the insights you need to make data-driven decisions.
What models does ExplaiNER support?
ExplaiNER supports a wide range of models, including popular frameworks like TensorFlow, PyTorch, and Scikit-learn.
Can I compare multiple models at once?
Yes, ExplaiNER allows you to upload and compare multiple models simultaneously, making it easy to identify the best-performing solution for your needs.
How do I access historical benchmarking data?
Historical data is stored automatically in ExplaiNER. You can retrieve it by navigating to the "Reports" section and selecting the desired date or model configuration.