Fine-tuned, quantized LLMs achieve about 93% accuracy on an internal RoboCup@Home planning benchmark and run locally on Jetson hardware.
Palm-e: An embodied multimodal language model,
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RDMM: Fine-Tuned LLM Models for On-Device Robotic Decision Making with Enhanced Contextual Awareness in Specific Domains
Fine-tuned, quantized LLMs achieve about 93% accuracy on an internal RoboCup@Home planning benchmark and run locally on Jetson hardware.