Enhancing Generative AI Deployment: FriendliAI and Hugging Face Partnership

A Collaboration to Advance AI Innovation

In the fast-evolving world of artificial intelligence, partnerships are key to unlocking new possibilities. Hugging Face, a powerhouse in AI development, has joined forces with FriendliAI, a leader in accelerated generative AI inference. This collaboration aims to enhance the way developers deploy and manage AI models, making significant strides in simplifying workflows and providing cutting-edge tools for the community.

With a shared vision of empowering developers, researchers, and businesses, this partnership introduces FriendliAI Endpoints as a new deployment option within the Hugging Face Hub. This integration not only simplifies the deployment process but also ensures that developers have direct access to high-performance and cost-effective inference infrastructure.

Revolutionizing Model Deployment

FriendliAI has already made waves in the industry by integrating with the Hugging Face platform, enabling users to deploy Hugging Face models seamlessly. This integration provides access to thousands of supported open-source models, along with the capability to deploy private models effortlessly. The extensive list of supported model architectures is readily available, showcasing the versatility of this collaboration.

Now, with the latest update, deploying models has never been easier. Users can enjoy a one-click deployment experience directly from the Hugging Face Hub. By simply selecting the “Deploy this model” option on the model card, developers can use their Friendli Suite accounts to access powerful deployment capabilities.

This streamlined process leads developers to FriendliAI’s model deployment page, where they can deploy models on NVIDIA H100 GPUs. The intuitive interface allows for easy setup of Friendli Dedicated Endpoints, a managed service designed for generative AI inference. While deployments are underway, users can interact with open-source models directly on the page, making it simple to explore and test their capabilities in real-time.

Deploy Models with NVIDIA H100 in Friendli Dedicated Endpoints

The collaboration leverages FriendliAI’s advanced GPU-optimized inference engine, enabling developers to deploy open-source or custom models on NVIDIA H100 GPUs through the Dedicated Endpoints service. By clicking “Deploy now” on the model deployment page, users can access fast and cost-effective inference without the hassle of managing infrastructure.

Although H100 GPUs are powerful, operational costs can escalate quickly at scale. FriendliAI’s optimized service mitigates this issue by reducing the number of GPUs required while ensuring peak performance, significantly lowering overall costs. This not only enhances cost efficiency but also simplifies the complexities associated with infrastructure management.

Inference Open-Source Models with Friendli Serverless Endpoints

For developers seeking a more flexible approach, Friendli Serverless Endpoints offer a user-friendly solution for efficiently inferring open-source models. This service provides easy-to-use APIs for models optimized by FriendliAI, delivering high performance at a low cost. Users can directly chat with these powerful open-source models on the model deployment page, enhancing the interactive experience.

What’s Next for AI Development

The partnership between Hugging Face and FriendliAI marks a significant milestone in making open-source AI more accessible to developers worldwide. By offering high-speed, cost-efficient inference solutions, FriendliAI is eliminating the complexities of infrastructure management, allowing users to focus on what truly matters—innovation.

As we move forward, both Hugging Face and FriendliAI remain committed to transforming how AI is developed. This collaboration paves the way for groundbreaking innovations that will shape the next era of artificial intelligence. For those interested in staying updated about future developments, following the Hugging Face organization page is a great way to keep in the loop.