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feat(compression): reject empty compression spec (#3678) 
An empty spec list passed to compress() previously returned an
unmodified model silently. Fail early with a clear error instead,
since an empty spec is almost certainly a mistake.

BUG=part of #3256
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tensorflow feat(compression): reject empty compression spec (#3678) 2026-08-24 23:11:41 +00:00
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README.md Added Error Handling & Defensive Programming Guide (#3539) 2026-06-30 22:24:50 +00:00
SECURITY.md
tflite_micro.py

README.md

TensorFlow Lite for Microcontrollers

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:

Build Status

CI Status

Group Status
Core CI CI Sync
Targets Cortex-M RISC-V Hexagon Xtensa
Misc Generate Integration Test

Community Supported TFLM Examples

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

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

Contributing

See our contribution documentation.

Getting Help

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.:

Additional Documentation

RFCs

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