This is a fantastic resource for developers interested in experimenting with multiple LLMs without the overhead of setting up separate environments. However, as @imjonse mentioned, it seems that the notebook calls out to proprietary APIs, meaning the heavy lifting isn't happening entirely within Colab. Can anyone shed light on which parts are executed externally versus locally? Also, are there open-source alternatives that allow for fully local fine-tuning and deployment within Colab or other accessible platforms?
For sure, the request is going to a proprietary API for heavy lifting but the idea of this colab notebook is to extend the possibility of running 100s of experiments by calling out an API that handles the experiments as requested while the colab notebook becomes that single session of performing experiments on different models, hyperparameters and datasets, perform evals on all and get one final deployment.