Registry / ai-ml / tflite-runtime

tflite-runtime

library2.14.0pypypiunverified

TensorFlow Lite Runtime is a lightweight library for on-device machine learning inference, optimized for mobile and embedded devices. Version 2.14.0 supports model conversion and execution with hardware acceleration. Releases are tied to TensorFlow Lite versions.

ai-ml

pip install tflite-runtime

package ↗homepage ↗

INSTALL

IMPORT

SIG · TFLITE-RUNTIME

tflite-runtime

ai-mlpythonv2.14.0

Install

3.9s avg

Import

230ms

Disk

98MB

Pass rate

3/ 10

Env Coverage3 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.14.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✕ build_error

✓ 3.6s

py 3.11

✕ build_error

✓ 3.6s

py 3.12

✕ build_error

py 3.13

✕ build_error

py 3.9

✕ build_error

✓ 4.4s

98MB installed

● package 98MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Interpreter

✓ from tflite_runtime.interpreter import Interpreter

✗ from tflite_runtime import Interpreter

Interpreter is in tflite_runtime.interpreter module, not top-level.

load_delegate

✓ from tflite_runtime.interpreter import load_delegate

Use for GPU or Edge TPU delegates.

Basic inference with TFLite Runtime.

import numpy as np from tflite_runtime.interpreter import Interpreter interpreter = Interpreter(model_path='model.tflite') interpreter.allocate_tensors() input_details = interpreter.get_input_details() output_details = interpreter.get_output_details() input_data = np.array([[1.0, 2.0, 3.0]], dtype=np.float32) interpreter.set_tensor(input_details[0]['index'], input_data) interpreter.invoke() output_data = interpreter.get_tensor(output_details[0]['index']) print(output_data)

Debug

Known issues

breakingtflite_runtime does not include training ops. If your model uses custom ops or training-only ops, inference may fail.

fix

Use full TensorFlow for training; export to TFLite and ensure ops are supported.

affects: all

gotchaThe Interpreter class must be imported from tflite_runtime.interpreter, not from top-level tflite_runtime. Common mistake: `from tflite_runtime import Interpreter` -> AttributeError.

fix

Use `from tflite_runtime.interpreter import Interpreter`.

affects: all

deprecatedSupport for Python 3.6 ended in tflite-runtime 2.7. Check your Python version if you encounter installation errors.

fix

Upgrade to Python 3.7+ or use an older tflite-runtime version if absolutely necessary.

affects: >=2.7

Upgrade

Version history

2.14.0latest on PyPI · released Oct 3, 2023

Audit

Dependencies

No dependency data recorded yet.

Agent activity

24 hits · last 30 days

node

OpenAI (training)

Resources

packagehttps://pypi.org/project/tflite-runtime/ ↗

homepagehttps://www.tensorflow.org/lite/ ↗