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.
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.
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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.
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.
Source: PRWeb
