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  1. colab.research.google.comGoogle Colab

    Colab notebooks execute code on Google's cloud servers, meaning you can leverage the power of Google hardware, including GPUs and TPUs, regardless of the power of your machine. All you need...

  2. Feb 22, 2018 · from google.colab import files #For model json model_json = model.to_json() with open("model1.json","w") as json_file: json_file.write(model_json) files.download("model1.json") #For weights model.save('weights.h5') files.download('weights.h5')

  3. View source on GitHub. Download notebook. Model progress can be saved during and after training. This means a model can resume where it left off and avoid long training times. Saving also...

  4. Introduction. A Keras model consists of multiple components: The architecture, or configuration, which specifies what layers the model contain, and how they're connected. A set of weights...

  5. Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education.

  6. Jul 24, 2020 · Importing a dataset and training models on the data in the Colab facilitate the coding experience. We can apply different ways to import and download data in Colab. In this tutorial, I will discuss my experience in: Importing data from Google Drive; Importing and downloading data into the local system; Mounting Google Drive

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  8. Oct 25, 2020 · It's this simple: from google.colab import files. files.download('example.txt') . How to download files from Google Colab to your computer. where example.txt should be the file we want to download – in our case, we need to replace this with the path to our weights file.