Evaluate model predictions with TruLens
Calculate GPU requirements for running LLMs
Convert Hugging Face models to OpenVINO format
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
Browse and submit LLM evaluations
Request model evaluation on COCO val 2017 dataset
Display LLM benchmark leaderboard and info
Compare code model performance on benchmarks
Calculate memory usage for LLM models
Display and submit LLM benchmarks
Evaluate and submit AI model results for Frugal AI Challenge
Measure BERT model performance using WASM and WebGPU
Evaluate open LLMs in the languages of LATAM and Spain.
Trulens is a powerful tool designed for model benchmarking and evaluation. It allows users to assess and compare the performance of AI models, providing deep insights into their predictions and behaviors. Whether you're a developer, researcher, or data scientist, Trulens helps you understand and improve your models with precision.
• Model Benchmarking: Compare multiple models across different datasets and metrics.
• Performance Evaluation: Gain detailed insights into model accuracy, reliability, and robustness.
• Transparency: Uncover how models make predictions and identify potential biases.
• Customization: Define specific metrics and parameters to suit your needs.
• Integration: Works seamlessly with popular machine learning frameworks.
What types of models does Trulens support?
Trulens supports a wide range of AI models, including classification, regression, and deep learning models.
Do I need prior machine learning expertise to use Trulens?
No, Trulens is designed to be user-friendly. While some understanding of machine learning concepts is helpful, the tool simplifies the benchmarking process.
Can Trulens work with frameworks like TensorFlow or PyTorch?
Yes, Trulens is compatible with popular frameworks such as TensorFlow, PyTorch, and Scikit-learn, making it versatile for different workflows.