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The problem is that my performance is decreasing. I have made all the required changes to the code as advised by E17. However, none of these changes seem to be helping. I can't even get the code to run. Pre-trained models | Using data from a training dataset. I am not sure if this is actually a good thing. E17 says that if there is no attached data sources and the model is pre-trained, the compute will be used for training. But I don't understand how this is supposed to work. If there is no attached data sources, No pre-trained models | Using data from a training dataset. This should be okay. E17 says that if there are no pre-trained models, the compute will not be used for training. But I am still getting the error. Make sure that you have a valid or default Account with the Kaggle website. Make sure that you have the right number of cores available on your VM. E17 allows you to automatically scale to all the available cores. You need at least 1 core and should keep the number of cores the same in all your notebooks. If you don't have the right number of cores, the notebook will be slower and you will get an error. Notebook ID | Use this notebook ID if you have trouble. Possible causes | Use this section to list possible causes for the problem. You can also edit this section to add more causes. Import Extra_KaggleNotebooks.ipynb when you have trouble. Solution Run the following code in the Command Prompt or Terminal window to import this notebook and load the pre-trained model. Share this page Recommended reading Kaggle is a platform that allows you to run and share your algorithms and models on a massive scale with the world. Kaggle allows you to collaborate with other users, win prizes, and share the benefits. The platform is a one-stop-shop to develop, test, and deploy models that process petabytes of data and predict analytics that are critical to many
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