![]() ![]() ![]() autogluon : An OVHcloud preset image containing JupyterLab notebook, Visual Studio Code IDE and AutoGluon + mxnet libraries.Fast.ai : An OVHcloud preset image containing JupyterLab notebook, Visual Studio Code IDE and fast.ai libraries. ![]() MXNet : An OVHcloud preset image containing JupyterLab notebook, Visual Studio Code IDE and mxnet libraries.Hugging Face Transformers : An OVHcloud preset image containing JupyterLab notebook, Visual Studio Code IDEand hugging face libraries.Tensorflow 2 : An OVHcloud preset image containing JupyterLab notebook, Visual Studio Code IDE and tensorflow 2 libraries.PyTorch : An OVHcloud preset image including JupyterLab notebook, Visual Studio Code IDE and pytorch libraries.You can choose the configuration that best suits your needs among them.Ĭurrently the following configurations are available : Notebooks are daemon jobs, meaning that they will run indefinitely until the user request an interuption.ĪI Training offers several notebooks images with different configurations. Step 2 - Select the notebook corresponding to your needsĪ job is basically a Docker container that is run within the OVHcloud infrastructure. Instructions Step 1 - Begin as classic job submissionįollow the same steps as a classic job submission described here until you reach the Step 5 - Providing a Docker image. an AI Training project created inside a public cloud project.This guide covers the process of starting a simple interactive notebook leveraging GPUs over AI Training service. ![]()
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