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.

pip install tflite-model-maker

If you want to install nightly version tflite-model-maker-nightly, please follow the command:

pip install tflite-model-maker-nightly
  • 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 0.2.4.dev202011032146

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 0.2.4.dev202011032146
File Size Uploaded
tflite-model-maker-nightly-0.2.4.dev202011032146.tar.gz 54.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for tflite-model-maker-nightly 0.2.4.dev202011032146
File Interpreter ABI Platform
tflite_model_maker_nightly-0.2.4.dev202011032146-py3-none-any.whl Python 3 none any Details

Total release size: 169.6 kB

Release files / tflite-model-maker-nightly-0.2.4.dev202011032146.tar.gz

Download URL tflite-model-maker-nightly-0.2.4.dev202011032146.tar.gz
Size 54.7 kB
Tags Source
SHA-256 checksum
How to use checksums
76df377105215d0fb80238a6c37984f21af1fdd576b1ee9d8cb1b6defcd634b2
BLAKE2b-256 checksum
How to use checksums
25df2d540643d620a888584f3a8f1222f0c4eb471e05fa54efc9cb3f0240c33d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.9

Release files / tflite_model_maker_nightly-0.2.4.dev202011032146-py3-none-any.whl

Download URL tflite_model_maker_nightly-0.2.4.dev202011032146-py3-none-any.whl
Size 114.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f4b40b9fe8078e9047e936fad2e43581e97ffc7a46e2e80ce413c4e193101a32
BLAKE2b-256 checksum
How to use checksums
7cf6d969a9cadbfe03ba838e51815be79f5c1aab5578d8dad7b50ec53a832f58
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/50.3.2 requests-toolbelt/0.9.1 tqdm/4.51.0 CPython/3.7.9

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