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How Microsoft is bringing Meta’s advanced AI model, Llama 2 to Azure customers

Llama 2: AI model that transforms text and image processing comes to Azure


In a groundbreaking collaboration, Microsoft has teamed up with Meta, the tech giant behind Instagram, Facebook, and WhatsApp, to Azure customers. Llama 2 is trained with 40% more data than its predecessor and has twice the context extension.

This model also allows realistic images to be generated from textual descriptions. This AI processes language, images, and data accurately and efficiently.


In this article, we will explore the importance of this tool, its capabilities, and how Azure users can integrate this cutting-edge technology into their projects.

The Power of Llama 2

It is the result of Meta’s experience in developing large-scale AI models with diverse functionalities.

This revolutionary model can multi-task in different domains, taking AI research capabilities to new levels.

Among its impressive abilities, it can answer questions, generate captions, classify images, and much more, making it an end-to-end AI solution.

Microsoft’s Azure Alliance

Recognizing the potential of Llama 2, Microsoft has taken a bold step by integrating this innovative AI model into its Azure Machine Learning service.

This strategic decision opens up new possibilities for Azure users, allowing them to leverage it in their applications and experiments.

With this partnership, Microsoft aims to foster innovation and discovery in various industries and fields of study.

In addition, Microsoft seeks to drive the development and experimentation of new artificial intelligence algorithms that can benefit from the use of Llama 2. This model offers some unique and differentiating features, such as its multilingual capability, thematic versatility, and computational efficiency, which make it more suitable for certain tasks and applications than other existing models, such as OpenAI’s well-known GPT.

How to use Llama 2 in Azure

This AI model is now available in the model catalogue in Azure Machine Learning. The model catalogue, currently in public preview in Azure Machine Learning, is its hub for fundamental models, and allows users to easily discover, customise and operationalise large fundamental models at scale.


Native support for Llama 2 within the Azure Machine Learning model catalogue allows users to use these models without having to manage any of the infrastructure or environment dependencies. It offers built-in support for fine-tuning and model evaluation, including a selection of optimisation libraries such as DeepSpeed and ORT (ONNX RunTime), which accelerate fine-tuning, along with LoRA (Low-Range Adaptation of Large Language Models) to greatly reduce the memory and compute requirements for fine-tuning.

For Azure customers wishing to explore the capabilities of Llama 2, the process is simple. Accessing and using it only requires an Azure account and an Azure Machine Learning workspace.

Once set up, users can create a compute instance and easily install the Llama 2 Python package.

To facilitate experimentation, Azure Machine Learning Studio allows users to create and run experiments seamlessly.

For detailed guidelines on how to employ Llama 2 in Azure, the official documentation provides step-by-step instructions.

The future with Llama 2 and Azure

The collaboration between Microsoft and Meta has enabled the creation of Llama 2, a leading AI model with multiple functionalities.

By integrating it into Azure Machine Learning, Microsoft facilitates cutting-edge AI research and application development. Harness the power of Llama 2 and embark on a journey of exploration, innovation and transformative AI-driven projects.

Using AI models requires a dedication of resources, time and expertise that is not always available to every team. If you need help, looking for an expert Partner is your best option. At Itequia we have been creating innovative digital solutions for more than 15 years and we will be happy to answer your questions and help you! Contact us!

Itequia Team