{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/16"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/9"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/19"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/9"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"}],"enrichment":{"capability":"TensorFlow Lite runtime enables on-device machine learning inference on mobile and embedded devices with low latency and minimal binary size.","skillfed_tags":["edge-inference","model-deployment","embedded-ml"],"use_cases":["Run pre-trained image classification or object detection models on Raspberry Pi or ARM-based edge devices.","Deploy real-time inference pipelines on mobile devices without the overhead of the full TensorFlow library.","Execute quantized or pruned models for resource-constrained IoT and embedded systems.","Integrate lightweight neural networks into Python applications on ARM architectures (aarch64, armv7l).","Prototype and test model inference performance on edge hardware before production deployment."],"what_it_does":"TensorFlow Lite runtime is the official inference engine for running pre-trained machine learning models on mobile and embedded devices. It is designed to execute models with minimal latency and a small footprint, supporting Android, iOS, and other operating systems. The package provides Python bindings to load and run .tflite model files, making it suitable for edge deployment scenarios where full TensorFlow would be too heavy.\n\nThe package depends only on numpy and ships as platform-specific wheels for common architectures (x86_64, aarch64, armv7l) across Python 3.8\u20133.11. It is classified as Production/Stable and carries no known security vulnerabilities, though the package has been dormant since its last release on 2023-10-03.","worth_installing":"Yes, if you have a pre-converted .tflite model and need to run inference on mobile or embedded devices. The package is stable, lightweight, and carries no known vulnerabilities. However, the dormant maintenance status means no recent updates or security patches; verify compatibility with your target model format and hardware before committing to production use."},"id":"tflite-runtime","links":{"html":"https://skillfed.io/packages/tflite-runtime","md":"https://skillfed.io/packages/tflite-runtime.md","pypi":"https://pypi.org/project/tflite-runtime/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-10-03","license_spdx":null,"license_treatment":"permissive","name":"tflite-runtime","python_support":"unspecified","summary":"TensorFlow Lite is for mobile and embedded devices."},"popularity":{"monthly_downloads":120678,"position":12013,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.14.0"}