Github Eleutherai Hae Rae Repository for the hae rae project, a project to improve the reasoning and instruction following abilities of polyglot ko. this repository hosts datasets, blog posts, and code from our progress. Our mission is to advance the field with insightful benchmarks and tools. founded in may 2023, we have published widely used benchmarks (hae rae bench and kmmlu) and are contributing to push korean llm research.
Eleutherai Github The hae rae bench 1.0 is the original implementation of the dataset froom the paper: hae rae bench paper. the benchmark is a collection of 1,538 instances across 6 tasks: standard nomenclature, loan word, rare word, general knowledge, history and reading comprehension. As models get smarter, humans won't always be able to independently check if a model's claims are true or false. we aim to circumvent this issue by directly eliciting latent knowledge (elk) inside the model’s activations. eleutherai has trained and released many powerful open source llms. Dedicated to analyzing extended korean chain of thought reasoning. includes hae rae bench, kmmlu, kudge, click, k2 eval, hrm8k, benchhub, kormedqa, kbl and more. best of n, majority voting, beam search, and other advanced methods. supports openai compatible endpoints, huggingface, and litellm. To bridge this gap for the korean language, we introduce hae rae bench, a dataset curated to challenge models lacking korean cultural and contextual depth. the dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension.
Gae Rae Github Dedicated to analyzing extended korean chain of thought reasoning. includes hae rae bench, kmmlu, kudge, click, k2 eval, hrm8k, benchhub, kormedqa, kbl and more. best of n, majority voting, beam search, and other advanced methods. supports openai compatible endpoints, huggingface, and litellm. To bridge this gap for the korean language, we introduce hae rae bench, a dataset curated to challenge models lacking korean cultural and contextual depth. the dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension. Pythia public the hub for eleutherai's work on interpretability and learning dynamics jupyter notebook • apache license 2.0 • 180 • 2.4k • 25 • 3 •updated dec 5, 2024 dec 5, 2024. To bridge this gap for the korean language, we introduce hae rae bench, a dataset curated to challenge models lacking korean cultural and contextual depth. the dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension. This website is an informational site for the sosd dataset, and serves as the official mit dsg host of sosd benchmark results. To bridge this gap for the korean language, we introduce the hae rae bench, a dataset curated to challenge models lacking korean cultural and contextual depth. the dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension.
Github Hae Rae Haerae Evaluation Toolkit The Most Modern Llm Pythia public the hub for eleutherai's work on interpretability and learning dynamics jupyter notebook • apache license 2.0 • 180 • 2.4k • 25 • 3 •updated dec 5, 2024 dec 5, 2024. To bridge this gap for the korean language, we introduce hae rae bench, a dataset curated to challenge models lacking korean cultural and contextual depth. the dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension. This website is an informational site for the sosd dataset, and serves as the official mit dsg host of sosd benchmark results. To bridge this gap for the korean language, we introduce the hae rae bench, a dataset curated to challenge models lacking korean cultural and contextual depth. the dataset encompasses six downstream tasks across four domains: vocabulary, history, general knowledge, and reading comprehension.
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