I recently expanded a project that allows for easy benchmarking of local language models, specifically for Named Entity Recognition (NER) tasks. By using a simple JSON configuration, you can now evaluate and compare the performance of different models installed through Ollama without the need for extensive coding.<p>The idea is to make it easier for developers and data scientists to test various models and see how they perform on specific tasks, all within a streamlined framework.<p>If you're interested in learning more about the approach and trying it out, you can check out the full details in my blog post: Creating a JSON Framework to Test Local Language Models for NER — <a href="https://datasignal.uk/blog/ner-framework.html" rel="nofollow">https://datasignal.uk/blog/ner-framework.html</a><p>The code is open source and available on GitHub: NER-llm-blog Repo — <a href="https://github.com/DataSignalOrg/NER-llm-blog/tree/master">https://github.com/DataSignalOrg/NER-llm-blog/tree/master</a><p>I’d love to hear your thoughts or suggestions for improvements!