Learn how to set up the Raspberry Pi AI Kit with the new Raspberry Pi 5. The kit allows you to explore machine learning and AI concepts using Python and TensorFlow.
This article discusses how to test small language models using 3.8B Phi-3 and 8B Llama-3 models on a PC and Raspberry Pi with LlamaCpp and ONNX. Written by Dmitrii Eliuseev.
• This is an MCU-based vision AI module powered by Arm Cortex-M55 and Ethos-U55, supporting TensorFlow and PyTorch frameworks.
• It has a standard CSI interface, onboard digital microphone, and SD card slot.
• Compatible with XIAO series, Arduino, Raspberry Pi, and ESP dev board.
• Supports off-the-shelf and custom AI models from SenseCraft AI, including Mobilenet V1, V2, Efficientnet-lite, Yolo v5 & v8.
• Can be used for industrial automation, smart cities, transportation, smart agriculture, and mobile IoT devices.
• It has a standard CSI interface, onboard digital microphone, and SD card slot.
• Compatible with XIAO series, Arduino, Raspberry Pi, and ESP dev board.
• Supports off-the-shelf and custom AI models from SenseCraft AI, including Mobilenet V1, V2, Efficientnet-lite, Yolo v5 & v8.
• Can be used for industrial automation, smart cities, transportation, smart agriculture, and mobile IoT devices.
- Shows how an individual can use Python for speech recognition (SR), Push-to-- Talk (PTT) systems, and large action models to create their own AI assistant.
- Describes the process of creating a "la Rabbit prototype" with Python code on Raspberry Pi hardware.
- Emphasizes how these components can be combined for various tasks using different APIs like OpenAI or LLaMA (Large Language Model from Meta).
- Describes the process of creating a "la Rabbit prototype" with Python code on Raspberry Pi hardware.
- Emphasizes how these components can be combined for various tasks using different APIs like OpenAI or LLaMA (Large Language Model from Meta).
