# Week 7 - Evaluation of LLM outputs and structured outputs



### today's schedule

* Quiz
* Short Recap
* Short presentation of current status
* Breakout Session ‘Next Steps’
* Homework for next week





### resources

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### homework

* Take a look at this article: [https://blog.n8n.io/open-source-llm/](https://blog.n8n.io/open-source-llm/)&#x20;
* Take a look at some open-source / open-access LLM frameworks:
*
  * Ollama (Mac, Linux):
    * [https://www.youtube.com/watch?v=Ox8hhpgrUi0](https://www.youtube.com/watch?v=Ox8hhpgrUi0)
    * [https://www.youtube.com/watch?v=k\_1pOF1mj8k](https://www.youtube.com/watch?v=k_1pOF1mj8k)&#x20;
  * LM Studio (Windows, Mac, Linux): - --[https://medium.com/@genebernardin/running-llms-locally-using-lm-studio-38070f286413](https://medium.com/@genebernardin/running-llms-locally-using-lm-studio-38070f286413)&#x20;
  * GPT4All
* Test some open-source/open-access LLMs either locally downloaded or in HuggingFace spaces or any other test environment (e.g. HuggingChat, H2O.ai, etc.)
  * Do you see significant differences in the output of proprietary and open-source/open-access LLMs?

