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Use API to automate training, deployment of your AI pipelines.
Deploy apps like Gradio, Streamlit, fastapi and more on GPU powered instances.
A simple UI to set up a GPU powered instance in few clicks.
Choose from world's fastest Nvidia GPU A100, A6000 and A5000.
Choose a predefined instance / public container. Access instance through Jupyter Lab, VScode or SSH
Increase/Decrease GPU, switch to a different GPU type for faster training.
Quickly automate your instance lifecycle for training and deploying your AI model using our python API.
//Instantiate blazing fast GPU with your favourite ML library/framework.
instance = Instance.create(gpu_type='A100',
instance.url //Get JupyterLab URL
instance.ssh_str // Get SSH string to connect to VS code
//Free up GPU/memory resources while persisting all data and models to disk
//Scale up number of GPU or switch to faster one while resuming your GPU instance
// Free up the resources and stop billing.
Instantiate blazing fast GPU with your favourite ML library/framework.
Connect to Instance
Connect to JupyterLab or VScode through SSH.
Free up resources GPU and memory while persisting all data and models to disk.
Increase number of GPU or switch to faster one to train your workload efficiently while resuming GPU instance.
Free up the resources and stop billing. Deletes the data and models