In the development of artificial intelligence, the application of Large Language Model (LLM) Single Board Computers (SBC) and AI sensors is becoming increasingly widespread. This article will detail the performance tests and tutorials of high-performance SBCs such as the NVIDIA Jetson AGX Orin 64GB Developer Kit, Raspberry Pi, LattePanda Alpha / Delta / Sigma Single Board Computers and explore how to deploy and run various LLMs on these platforms. In addition, we will introduce some easy-to-use AI cameras and voice recognition sensors, as well as their applications in innovative projects.
Deploy and run LLM on LattePanda Sigma (LLaMA, Alpaca, LLaMA2, ChatGLM)
This article provides a comprehensive guide on deploying and running various Large Language Models (LLMs) on the LattePanda Sigma, a single-board computer. It offers insights into choosing the right LLM, the process of running LLMs, and the key steps and considerations for optimizing the use of AI with limited hardware resources.
Deploy and run LLM on Lattepanda 3 Delta 864 (LLaMA, LLaMA2, Phi-2, ChatGLM2)
This detailed guide on deploying and running popular Large Language Models (LLMs) on the Lattepanda 3 Delta 864, including LLaMA, LLaMA2, Phi-2, and ChatGLM2.
Deploy and run LLM on Raspberry Pi 5 vs Raspberry Pi 4B (LLaMA, LLaMA2, Phi-2, Mixtral-MOE, mamba-gp
This is a comprehensive guide on deploying and running various Large Language Models (LLMs) on the Raspberry Pi 5 8GB, comparing its performance with the Raspberry Pi 4 model B. It offers insights into choosing the right LLM, the process of running LLMs, and the key steps and considerations for optimizing the use of AI with limited hardware resources.
Test Report and Tutorial: LLaMA2-7b and LLaMA2-13b Performance
This guide presents a performance test report for the NVIDIA Jetson AGX Orin 64GB Developer Kit, focusing on its capabilities in large language model inference.
It provides a detailed analysis of the device's performance with different models and quantization methods, offering insights into its potential applications in AI and machine learning.
Running LLaMA 7B on a 8 GB RAM LattePanda Alpha
This guide offers insights into the specifications of the LattePanda Alpha, the process of running LLMs, and the key steps and considerations for optimizing the use of AI with limited hardware resources.
Deploy and run LLM on Raspberry Pi 4B (LLaMA, Alpaca, LLaMA2, ChatGLM)
This guide is on deploying and running various Large Language Models (LLMs) on the Raspberry Pi 4B, including LLaMA, Alpaca, LLaMA2, and ChatGLM.
NVIDIA Jetson Orin Nano 8GB Developer Kit
Features an NVIDIA Ampere architecture GPU with 1024 CUDA cores, 32 third-generation Tensor Cores, and a 6-core Arm CPU.
SKU: DFR1078
Running a ChatGPT-Like LLM-LLaMA2 on a Nvidia Jetson Cluster
This project allows you to use a ChatGPT-like Large Language Model - LLaMA2 on an NVIDIA Jetson cluster.
Building an AI Assistant on Unihiker Single Board Computer with ChatGPT API and Azure Speech API
The guide is on building an AI desktop assistant using OpenAI's GPT technology and Azure Speech API on the Unihiker device. It offers insights into the hardware setup, software programming, and the key steps for creating an intelligent voice desktop agent.
DIY Line Tracking Robot with Huskylens and Romeo
This project will demonstrate the line tracking function of Huskylens, and will install HuskyLens to a Devastator tank mobile robot, then Huskylens will control the robot to perform line tracking.
Gravity: Offline Language Learning Voice Recognition Sensor for Arduino / Raspberry Pi / Python / ESP32 - I2C & UART
Compatible with multiple controllers, providing a flexible solution for voice interaction in various applications such as smart home appliances and robotics projects.
SKU: SEN0539-EN
Smart Waiter - Intelligent Voice Assistant in Restaurant
Restaurant/Hotel Food ordering System using Voice Assistant. Using DFRobot Offline Language Learning Voice Recognition Sensor