Microsoft Introduces Multimodal SLMs Trained on NVIDIA GPUs

Microsoft has introduced the most recent additions to its Phi household of small language fashions (SLMs), that includes the brand new Phi-4-multimodal and Phi-4-mini fashions, each educated utilizing NVIDIA GPUs. This growth marks a major step within the evolution of language fashions, specializing in effectivity and flexibility, in keeping with NVIDIA.

Developments in Small Language Fashions

SLMs have emerged as a sensible answer to the challenges posed by massive language fashions (LLMs), which, regardless of their capabilities, require substantial computational assets. SLMs are designed to function effectively inside constrained environments, making them appropriate for deployment on gadgets with restricted reminiscence and computational energy.

Microsoft’s new Phi-4-multimodal mannequin is especially noteworthy for its means to course of a number of sorts of information, together with textual content, audio, and pictures. This functionality opens up new prospects for functions corresponding to automated speech recognition, translation, and visible reasoning. The mannequin’s coaching concerned 512 NVIDIA A100-80GB GPUs over 21 days, underscoring the intensive computational efforts required to realize its capabilities.

Phi-4-multimodal and Phi-4-mini

The Phi-4-multimodal mannequin boasts 5.6 billion parameters and has demonstrated superior efficiency in automated speech recognition, rating first on the Huggingface OpenASR leaderboard with a phrase error charge of 6.14%. This achievement highlights the mannequin’s potential in enhancing speech recognition applied sciences.

Alongside Phi-4-multimodal, Microsoft additionally launched Phi-4-mini, a text-only mannequin optimized for chat functions. With 3.8 billion parameters, Phi-4-mini is designed to deal with long-form content material effectively, providing a context window of 128K tokens. Its coaching concerned 1024 NVIDIA A100 80GB GPUs over 14 days, reflecting the mannequin’s deal with high-quality academic information and code.

Deployment and Accessibility

Each fashions can be found on Microsoft’s Azure AI Foundry, offering a platform for designing, customizing, and managing AI functions. Customers may also discover these fashions by the NVIDIA API Catalog, which affords a sandbox setting for testing and integrating these fashions into numerous functions.

NVIDIA’s collaboration with Microsoft extends past simply coaching these fashions. The partnership contains optimizing software program and fashions like Phi to advertise AI transparency and help open-source tasks. This collaboration goals to advance AI expertise throughout industries, from healthcare to life sciences.

For extra detailed data, go to the NVIDIA weblog.

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