mirror of https://github.com/vee1e/tflite-micro - Infrastructure to enable deployment of ML models to low-powe
Find a file
Arpit Jain 5fa112687b
ci: declare workflow-level contents: read on 3 workflows (#3558)
Pins the default GITHUB_TOKEN to contents: read on the workflows in
.github/workflows/ that don't call a GitHub API beyond the initial
checkout. The other workflows in this directory are left implicit
because they need write scopes that a maintainer is better placed
to declare.

Motivation: CVE-2025-30066 (March 2025 tj-actions/changed-files
compromise) exfiltrated GITHUB_TOKEN from workflow logs. Per-workflow
caps bound runtime authority irrespective of repo or org default,
give drift protection if the default ever widens, and are credited
per-file by the OpenSSF Scorecard Token-Permissions check.

YAML validated locally with yaml.safe_load.

Signed-off-by: Arpit Jain <arpitjain099@gmail.com>
2026-06-30 16:47:20 -07:00
.github ci: declare workflow-level contents: read on 3 workflows (#3558) 2026-06-30 16:47:20 -07:00
ci No tensorflow 1 (#3546) 2026-05-06 18:31:12 +00:00
data/continuous_builds
docs [Doc] Fix typos (#3446) 2026-02-11 17:18:49 +00:00
python Format (#3577) 2026-05-27 06:39:06 -07:00
signal Bazel Module (#3364) 2026-02-11 14:11:47 -08:00
tensorflow feat(compression): add Huffman and Pruning compression support (#3612) 2026-06-30 22:53:59 +00:00
third_party [CI] Clean up bzl (#3478) 2026-02-12 14:05:54 -08:00
tools Clean-up unused bzl load (#3576) 2026-05-26 22:55:55 +00:00
.bazelignore Added bazelignore (#3398) 2026-01-31 15:40:35 -08:00
.bazelrc +build:windows_ci --build_python_zip=false (#3462) 2026-02-12 09:33:55 -08:00
.bazelversion Bazel 8.7.0 (#3610) 2026-06-30 15:23:57 -07:00
.clang-format
.editorconfig chore(editorconfig): add max_line_length for python files (#3225) 2025-10-17 10:00:56 -07:00
.gitignore
.style.yapf
AUTHORS
BUILD build(bazel): inject tflite_micro shim via tflm_py_* wrappers (#3573) 2026-05-26 19:51:58 +00:00
CODEOWNERS Updated owners (#3195) 2025-09-22 10:03:58 -07:00
CONTRIBUTING.md [Doc] Fix typos (#3446) 2026-02-11 17:18:49 +00:00
debugging_output.md
LICENSE
MODULE.bazel Bazel 8.7.0 (#3610) 2026-06-30 15:23:57 -07:00
MODULE.bazel.lock Bazel 8.7.0 (#3610) 2026-06-30 15:23:57 -07:00
README.md Added Error Handling & Defensive Programming Guide (#3539) 2026-06-30 22:24:50 +00:00
SECURITY.md
tflite_micro.py Bazel Module (#3364) 2026-02-11 14:11:47 -08:00

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