Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

TFLite Model Maker

Overview

The TFLite Model Maker library simplifies the process of adapting and converting a TensorFlow neural-network model to particular input data when deploying this model for on-device ML applications.

Requirements

  • Refer to requirements.txt for dependent libraries that're needed to use the library and run the demo code.

Installation

There are two ways to install Model Maker.

  • Install a prebuilt pip package.
pip install tflite-model-maker
  • Clone the source code from GitHub and install.
git clone https://github.com/tensorflow/examples
cd examples/tensorflow_examples/lite/model_maker/pip_package
pip install -e .

End-to-End Example

For instance, it could have an end-to-end image classification example that utilizes this library with just 4 lines of code, each of which representing one step of the overall process. For more detail, you could refer to Colab for image classification.

  1. Load input data specific to an on-device ML app.
data = ImageClassifierDataLoader.from_folder('flower_photos/')
  1. Customize the TensorFlow model.
model = image_classifier.create(data)
  1. Evaluate the model.
loss, accuracy = model.evaluate()
  1. Export to Tensorflow Lite model and label file in export_dir.
model.export(export_dir='/tmp/')

Notebook

Currently, we support image classification, text classification and question answer tasks. Meanwhile, we provide demo code for each of them in demo folder.

Release files for tflite-model-maker-nightly 0.1.2.dev202008101456

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tflite-model-maker-nightly 0.1.2.dev202008101456
File Size Uploaded
tflite-model-maker-nightly-0.1.2.dev202008101456.tar.gz 43.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for tflite-model-maker-nightly 0.1.2.dev202008101456
File Interpreter ABI Platform
tflite_model_maker_nightly-0.1.2.dev202008101456-py3-none-any.whl Python 3 none any Details

Total release size: 130.6 kB

Release files / tflite-model-maker-nightly-0.1.2.dev202008101456.tar.gz

Download URL tflite-model-maker-nightly-0.1.2.dev202008101456.tar.gz
Size 43.3 kB
Tags Source
SHA-256 checksum
How to use checksums
55265a31f64dbbd6c03a74d9c721c8a5680289d514896074fb94cbd16c02c9fa
BLAKE2b-256 checksum
How to use checksums
9b7324fc494c04149ae0128e63619e2c6f77557899ff16698c5b7d933f2f011c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.7

Release files / tflite_model_maker_nightly-0.1.2.dev202008101456-py3-none-any.whl

Download URL tflite_model_maker_nightly-0.1.2.dev202008101456-py3-none-any.whl
Size 87.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
380dfa18db2209f3834bdf5ca176fd1b5b39a2d93f0d39f255d485cf94836bb9
BLAKE2b-256 checksum
How to use checksums
47a988b3448a08e07a23f8f1ffba51cafc173c9ff6606461ef8797d643fef211
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.3.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.7

Release history Release notifications | RSS feed

This release
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page