• TensorFlow Lite for Microcontrollers
• Build Status
  • CI Status
  • Community Supported TFLM Examples
• Contributing
• Getting Help
• Additional Documentation
• RFCs

TensorFlow Lite for Microcontrollers is a port of TensorFlow Lite designed to run machine learning models on DSPs, microcontrollers and other devices with limited memory.

Additional Links:

• Tensorflow github repository
• TFLM at tensorflow.org

Group	Status
Core
Targets
Misc

This table captures platforms that TFLM has been ported to. Please see New Platform Support for additional documentation.

Platform	Status
Arduino
Coral Dev Board Micro	TFLM + EdgeTPU Examples for Coral Dev Board Micro
Espressif Systems Dev Boards
Ingenic MIPS Boards
Renesas Boards	TFLM Examples for Renesas Boards
Silicon Labs Dev Kits	TFLM Examples for Silicon Labs Dev Kits
Sparkfun Edge
Texas Instruments Dev Boards

See our contribution documentation.

A Github issue should be the primary method of getting in touch with the TensorFlow Lite Micro (TFLM) team.

The following resources may also be useful:

1. SIG Micro email group and monthly meetings.

2. SIG Micro gitter chat room.

3. For questions that are not specific to TFLM, please consult the broader TensorFlow project, e.g.:

   • Create a topic on the TensorFlow Discourse forum
   • Send an email to the TensorFlow Lite mailing list
   • Create a TensorFlow issue
   • Create a Model Optimization Toolkit issue

• Continuous Integration
• Benchmarks
• Profiling
• Memory Management
• Error Handling
• Logging
• Porting Reference Kernels from TfLite to TFLM
• Optimized Kernel Implementations
• New Platform Support
• Platform/IP support
  • Arm IP support
• Software Emulation with Renode
• Software Emulation with QEMU
• Compression
  • MNIST Compression Tutorial
• Python Dev Guide
• Automatically Generated Files
• Python Interpreter Guide

1. Pre-allocated tensors
2. TensorFlow Lite for Microcontrollers Port of 16x8 Quantized Operators