FriendliAI Integrates With Weights & Biases to Streamline Gen AI Deployment Workflows

FriendliAI and Weights & Biases Integration to bring ML Developers to enjoy seamless deployment

FriendliAI, the leading generative AI infrastructure company, announced an integration with Weights & Biases, the leading AI developer platform, to accelerate the development and deployment workflow for machine learning (ML) developers working with generative AI models.

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This collaboration empowers ML developers to seamlessly leverage Weights & Biases’s rich toolset while fine-tuning and deploying generative AI models on FriendliAI’s high-performance engine. FriendliAI’s comprehensive solution handles everything from resource management to efficient inference serving, catering to users across research and development (R&D) and production environments.

This integration enables developers to effortlessly deploy models trained on the Weights & Biases platform through FriendliAI’s dedicated endpoints. This alleviates the burden of manually loading Weights & Biases models onto serving engines through Python code to optimize them for specific use cases. By integrating all the essential components for a streamlined generative AI application lifecycle, developers can enjoy a smooth, efficient, and user-friendly experience for developing and deploying generative AI models.

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With this integration, we expect developers to be able to seamlessly deploy W&B Artifacts for production or testing purposes on the same Friendli endpoints while leveraging the Weights & Biases dashboard to monitor fine-tuning jobs running on Friendli Dedicated Endpoints.

This integration aims to streamline the ML developer workflow by leveraging FriendliAI’s highly-optimized infrastructure to deploy generative AI models stored on the Weights & Biases platform, allowing researchers to focus on pioneering new models instead of infrastructure management.

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