And you also need to set up report to wand b weights and biases. This is supported in the Onslaught and the multi-GPU branches and also in many of the Jupyter notebooks that are throughout all the branches of the advanced fine-tuning repo. Before I move to tips 8 and 9, I want to comment on scaling up. So I've talked about starting with a low number of rows, starting with LoRa or QLoRa, and starting with a small model. Well, here's the order you want to scale up in. Start by increasing the rows of data on a small model, then move QLoRa to LoRa.