How to Resolve RuntimeError in TensorFlow Lite for Microcontrollers on ESP32?
Hello everyone, I'm deploying a natural language processing (NLP) model on an ESP32 microcontroller using TensorFlow Lite for Microcontrollers. During inference, I encounter the error RuntimeError: Internal error: Failed to run model at node 13 with status 1. This error seems to occur randomly during different stages of text processing, particularly when processing longer input sequences. I've already applied model quantization, reduced the complexity of the input text, and ensured that the input data is properly formatted. What advanced debugging techniques or memory management strategies can I apply to resolve this runtime error? Are there specific configurations in TensorFlow Lite or best practices for managing memory on the ESP32 that can help improve the stability of NLP models?
The DevHeads IoT Integration Server accelerates technology engineering by helping pro devs learn, share and collaborate.
2,984Members
Resources
Similar Threads
Was this page helpful?
