Fortify Eval Suite
Shares tags: build, observability & guardrails, eval datasets
AI Tool
Unlock the Power of Language Models with HELM Benchmark Hub
Your go-to open benchmark repository for LLM tasks.
Evaluate top-tier language models with robust, scenario-based assessments.Access up-to-date and challenging datasets that reflect real-world requirements.Leverage transparent evaluations to make informed decisions for your projects.
Tags
BuildObservability & GuardrailsEval Datasets
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overview
What is HELM Benchmark Hub?
HELM Benchmark Hub is an open repository designed to assess the performance of leading language models across a variety of tasks. Our platform prioritizes transparency and reproducibility, allowing users to compare models' capabilities against a robust set of benchmarks.
- Covering dozens of LLM tasks.
- Accessible to researchers, enterprises, and policy makers.
- Utilizes cutting-edge evaluation datasets.
features
Key Features
The HELM Benchmark Hub integrates several advanced features to enhance your benchmarking experience. With our new HELM Capabilities leaderboard and refined scoring methods, achieving reliable evaluations has never been easier.
- Leaderboards showcasing real-time model performance.
- Mean score aggregation for consistency across evaluations.
- Regular updates with the latest datasets like MMLU-Pro and GPQA.
use_cases
Who Can Benefit from HELM?
HELM Benchmark Hub is tailored for a diverse range of users, from external practitioners analyzing model performance to enterprises making critical decisions about language model deployment. Our benchmark provides the clarity needed to select the best model for your specific use case.
- Researchers interested in reproducible results.
- Business decision-makers choosing language models for applications.
- Policy makers assessing AI technologies for ethical compliance.
Frequently Asked Questions
What types of tasks does HELM Benchmark Hub support?
HELM Benchmark Hub spans a wide range of LLM tasks, accurately reflecting real-world applications and challenges faced by language models.
How does the HELM leaderboard rank models?
Models on the HELM leaderboard are now ranked using a mean score (rescaled WB score), which enhances comparability and robustness across different evaluation scenarios.
Who should use HELM Benchmark Hub?
Our platform is designed for researchers, enterprises, and policy makers who require transparent and scenario-based evaluations of language models for informed decision-making.