Quick and simple training for AI models
Launch your AI training tasks in the cloud, without having to worry about how the infrastructure works. AI Training enables data scientists to focus on their core business, without having to worry about orchestrating computing resources.
This solution is built on the open-source Kubernetes platform, and enables you to train your models easily — in just a few clicks, or in the command line. Save time, increase your team’s productivity, and maintain the integrity of your sensitive data.
For developers and data scientists
Develop your models with your preferred framework, such as Scikit-learn, XGBoost or TensorFlow, then run training tasks on one or more GPU nodes in seconds. All you need to run is a single line of code or an API call.
Our solution manages usage planning for your GPU computing resources. This means you do not need to integrate it into your organisation.
GPU power at the best price
AI Training offers you the best prices on the market for GPU resources. Billing per minute is transparent, which makes it easier for you to manage your budget and optimise your spending.
Our GPU computing resources
|Description||Suitable for all AI training use cases|
|Applications||Deep learning training|
|GPU performance (FP32)||
|Number of cores||14 vCores|
|Public network||6Gbits/s (max)|
|Maximum number of GPUs per job||4|
What sets the AI Training solution apart
Simplicity to accelerate your AI projects
OVHcloud AI Training is a technology-neutral platform, based on the open-source Kubernetes platform. It enables you to optimise the use of GPU resources for your training, depending on your needs. This public cloud solution is commitment-free, pay-as-you-go, and dynamically adapts to your resource usage to offer you maximum flexibility and power. AI Training drastically improves productivity for data scientists, and simplifies day-to-day work by eliminating complex engineering tasks.
Lower costs, controlled billing
With AI Training, you get transparent pricing and access to the OVHcloud Control Panel, so you can easily track the cost of training tasks. This guarantees simplicity and predictability.
A European cloud that respects your data
Artificial intelligence opens up great opportunities for adding value to data, but it also requires end-to-end governance. Choosing a European cloud provider like OVHcloud ensures that your data is protected (GDPR), without the risk of a competitive breach caused by legislations such as the US Cloud Act.
Built on open and open-source standards
AI Training is natively compatible with industry-leading applications and frameworks, such as Scikit-learn, TensorFlow, Pytorch and Jupyter Notebook. Transparency is a key value of ours, and we promise total reversibility for your training processes.
Once you have created your Public Cloud project, you can launch your training tasks on computing resources directly via the OVHcloud Control Panel. You can do this via a Jupyter notebook, an API, or in the command line.
In just a few clicks, you can deploy a Jupyter notebook with the framework you want to use (TensorFlow, PyTorch, MxNet, etc.), or you can containerise your training code.
Via the OVHcloud Control Panel
Our web interface offers many features, including a dashboard to monitor your training, the ability to launch new training tasks, manage your data sets, and much more.
Via the command line
Example: You are looking to optimise a network of neurons that will help you classify your support tickets. This is how to deploy a JupyterLab with Pytorch, and your data, in two command lines.
Syncing your local data to your object storage
./ovhai data upload myBucket@GRA train.zip
Running a JupyterLab with Pytorch pre-installed and mounting data in /data read/write with 2 GPUs
./ovhai job run \
--gpu 2 \
--volume myBucket@GRA:/data:RW \
Automatic at the end of the job
Find out more
Please refer to our technical documentation for more details on how to use AI Training.
Submitting training tasks
Define the resources for your GPU computing tasks, and use them for AI Training. The solution works with Docker images from public or private templates. You can choose from a wide catalogue of templates to get started.
Orchestration and parallelisation
OVHcloud AI Training orchestrates GPU training on our infrastructure. Whether you are launching one task or several at once, your teams do not have to worry about hardware resource allocation, or GPU driver compatibility.
Compatible with TensorFlow, PyTorch, Scikit-learn, XGBoost and much more
If your AI models can leverage GPU resources in a containerised environment, AI Training is the perfect tool. No matter which application you use, our solution offers unparalleled simplicity in your GPU training tasks.
Compatibility with a large catalogue of pre-installed models
A large portfolio of public Docker images is available for free, making it even easier to get started.
Deploy images designed for deep learning (autoML on text, image or video), configured to harness the power of our GPUs.
Code via notebooks
Deploy pre-configured Jupyter notebooks for your preferred frameworks, such as TensorFlow, PyTorch, Scikit-learn, and more.
Managed from the OVHcloud Control Panel, via the API or in the command line
Depending on your skills and preference, you can launch and track your GPU computing tasks from the web interface, via the API, or via the command line. From Python to Java, Scala, C++ with Cuda, Golang, and much more — whatever programming language you want to use, anything is possible.
With quick access to your event logs, you can easily monitor your tasks.
OVHcloud AI Training billing
For each training task you launch, you pay per minute for the computing resources used, depending on their lifespan and the number of GPUs allocated.
No commitment is required to use this service.