by rentruewang · LLM 插件 · ★ 289
🫙 Archive This has topped the show HN front page link. This was born as a research project, and I think I have achieved most of what I set out to create. So today (2025/09/14) I'm archiving this repository. Nowadays I'm mainly working on , a deep learning algorithm compiler! Check it out. ☂️ BoCoEL Bayesian Optimization as a Coverage Tool for Evaluating Large Language Models 🤔 Why BoCoEL? Large language models are expensive and slow behemoths, and evaluating them on gigantic modern datasets only makes it worse.
| Stars | 289 |
| Forks | 16 |
| Language | Python |
| Category | LLM 插件 |
| License | BSD-3-Clause |
| Quality Score | 64.4795522551245/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-08 |
| Created | 2023-12-16 |
| Platforms | python |
| Est. Tokens | ~14k |
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bocoel is Bayesian Optimization as a Coverage Tool for Evaluating LLMs. Accurate evaluation (benchmarking) that's 10 times faster with just a few lines of modular code.. It is categorized as a LLM 插件 with 289 GitHub stars.
bocoel is primarily written in Python. It covers topics such as bayesian-optimization, benchmarking, evaluation.
You can find installation instructions and usage details in the bocoel GitHub repository at github.com/rentruewang/bocoel. The project has 289 stars and 16 forks, indicating an active community.
bocoel is released under the BSD-3-Clause license, making it free to use and modify according to the license terms.