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Evaluation collaboration with OpenCompass #426

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opened 2026-02-21 17:27:07 -05:00 by yindo · 0 comments
yindo commented 2026-02-21 17:27:07 -05:00
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Originally created by @tonysy on GitHub (Aug 23, 2023).

Originally assigned to: @takatost on GitHub.

Hi, thanks for the great works.

We are opencompass team(https://github.com/internLM/OpenCompass/), and focus on LLM evalaution.

OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features includes:

  • Comprehensive support for models and datasets: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 50+ datasets with about 300,000 questions, comprehensively evaluating the capabilities of the models in five dimensions.

  • Efficient distributed evaluation: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours.

  • Diversified evaluation paradigms: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue type prompt templates, to easily stimulate the maximum performance of various models.

  • Modular design with high extensibility: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded!

  • Experiment management and reporting mechanism: Use config files to fully record each experiment, support real-time reporting of results.

We would like to collaborate with dify on evaluation with opencompass. If you have any ideas or suggestions or plans, feel free to raise an issue or contact us with opencompass@pjlab.org.cn

OpenCompass Team

Originally created by @tonysy on GitHub (Aug 23, 2023). Originally assigned to: @takatost on GitHub. Hi, thanks for the great works. We are opencompass team(https://github.com/internLM/OpenCompass/), and focus on LLM evalaution. OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Its main features includes: - **Comprehensive support for models and datasets**: Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 50+ datasets with about 300,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. - **Efficient distributed evaluation**: One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. - **Diversified evaluation paradigms**: Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue type prompt templates, to easily stimulate the maximum performance of various models. - **Modular design with high extensibility**: Want to add new models or datasets, customize an advanced task division strategy, or even support a new cluster management system? Everything about OpenCompass can be easily expanded! - **Experiment management and reporting mechanism**: Use config files to fully record each experiment, support real-time reporting of results. We would like to collaborate with dify on evaluation with opencompass. If you have any ideas or suggestions or plans, feel free to raise an issue or contact us with opencompass@pjlab.org.cn OpenCompass Team
yindo closed this issue 2026-02-21 17:27:07 -05:00
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