Qualcomm has unveiled its AI Hub, an all-inclusive library of pre-optimized AI models ready to use on devices running on Snapdragon and Qualcomm platforms.
These models support a wide range of applications, including natural language processing, computer vision, and anomaly detection, and are designed to deliver high performance with minimal power consumption, a critical factor for mobile and desktop devices. Vanguard.
The AI Hub library currently includes more than 75 popular AI and generative AI models, including Whisper, ControlNet, Stable Diffusion, and Baichuan 7B. All models come in multiple runtimes and are optimized to take advantage of Qualcomm AI Engine hardware acceleration across all cores (NPU, CPU, and GPU). According to Qualcomm, they will offer four times faster inference times.
Documentation and tutorials provided.
AI Hub also automatically handles the translation of models from the source framework to popular runtimes. It works directly with the Qualcomm AI Engine Direct SDK and applies hardware-based optimizations. Developers can search for models according to their needs, download them and integrate them into their applications, saving time and resources.
AI Hub also provides tools and resources for developers to customize these models and fine-tune them using the Qualcomm Neural Processing SDK and the AI Model Efficiency Toolkit, both available on the platform.
To use AI Hub, developers need a trained model in PyTorch, TorchScript, ONNX, or TensorFlow Lite format, and a good understanding of the deployment target, which can be a specific device (such as the Samsung Galaxy S23 Ultra) or a variety of devices. . .
However, AI Hub is not exclusive to experienced developers. It also serves as a learning platform, providing comprehensive documentation and tutorials for those venturing into the world of AI.
Qualcomm plans to periodically update AI Hub with new models and support for additional platforms and operating systems. Developers can sign up to access these models on cloud-hosted devices based on Qualcomm platforms and get early access to new features and AI models.
