interbotix_ros_toolboxes VS wrapyfi

mkdir c:\ws\interbotics\src cd c:\ws\interbotics\src git clone -b noetic-devel https://github.com/ROBOTIS-GIT/dynamixel-workbench git clone -b melodic https://github.com/Interbotix/interbotix_ros_arms git clone --recursive https://github.com/xArm-Developer/xarm_ros git clone -b noetic https://github.com/Interbotix/interbotix_ros_manipulators git clone -b melodic-devel https://github.com/ROBOTIS-GIT/dynamixel-workbench-msgs git clone -b init_windows https://github.com/ms-iot/joystick_drivers git clone https://github.com/Interbotix/interbotix_ros_toolboxes cd c:\ws\interbotics catkin_make

The authors present an example of combining Wrapyfi (https://github.com/fabawi/wrapyfi), a Python wrapper for message-oriented and robotics middleware, with LLaMA (https://github.com/facebookresearch/llama), a series of large language models from Meta AI. They demonstrate how Wrapyfi can enable running LLaMA on multiple mid-range machines with high inference speed and low cost. They also provide links to their GitHub repository (https://github.com/modular-ml/wrapyfi-examples_llama) and paper (https://arxiv.org/abs/2302.09648) for more details. They state that this example can revolutionize natural language processing tasks such as text generation, summarization, question answering, sentiment analysis, etc. without having to buy new hardware and use their existing infrastructure!