Tensorflow lite TensorFlow Lite est un ensemble d'outils pour exécuter des modèles TensorFlow sur des appareils mobiles, intégrés et IoT. Las APIs de LiteRT contienen los mismos nombres de métodos que las APIs de TF Lite, por lo que migrar a LiteRT no requiere cambios de código detallados. Convert to a LiteRT model using the LiteRT converter. Durante la conversión, puedes aplicar optimizaciones como la cuantización para reducir el tamaño y la latencia del modelo con una pérdida de exactitud mínima o nula. The module provides classes and methods for interpreting, converting, optimizing and specifying target devices for TFLite models. See full list on geeksforgeeks. org Learn how to use the tf. lite module to convert, optimize and run TensorFlow models on TensorFlow Lite. Découvrez comment générer, convertir et exécuter des modèles TensorFlow Lite avec différentes plates-formes, langages et optimisations. TensorFlow Lite 是一个移动库，用于在移动设备、微控制器和其他边缘设备上部署模型。 查看指南 指南解释了 TensorFlow Lite 的概念和组件。 TensorFlow Lite モデルを生成するには、以下の方法があります。 既存の TensorFlow Lite モデルの使用: 既存のモデルを選択するには、TensorFlow Lite サンプルをご覧ください。モデルには、メタデータが含まれていてもいなくても構いません。 Las aplicaciones que usan bibliotecas de TF Lite seguirán funcionando, pero todo el desarrollo activo y las actualizaciones nuevas solo se incluirán en los paquetes de LiteRT. May 19, 2025 · LiteRT (short for Lite Runtime), formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI. The LiteRT system provides prebuilt and customizable execution environments for running models on Android quickly and efficiently, including options for hardware acceleration. Explore different ways to get a trained model, such as using pretrained models, training custom models, or converting TensorFlow models. In most cases, the API design reflects a preference for performance over ease of use. TensorFlow Lite is a lightweight solution for on-device machine learning models with fast performance and hardware acceleration. 0 许可证 授权，代码示例根据 Apache 2. Learn how to build, use and contribute to LiteRT from its GitHub repository. Aug 23, 2023 · Learn how to install and use TensorFlow Lite, a lightweight version of TensorFlow for edge devices, on Android, iOS, and Linux. LiteRT is the new name for TensorFlow Lite (TFLite), a trusted and open-source library for running AI models on edge devices. Sep 24, 2024 · TensorFlow inference APIs are provided for most common mobile and embedded platforms such as Android, iOS and Linux, in multiple programming languages. 將 TensorFlow 模型轉換成 TensorFlow Lite 模型：使用 TensorFlow Lite Converter，將 TensorFlow 模型轉換成 TensorFlow Lite 模型。 您可以在轉換時套用 最佳化設定 ，例如運用 量化 ，在不犧牲準確率的前提下縮減模型大小並減少延遲情況。 TensorFlow Lite Python 支持库 除另有说明外，本页内容根据 知识共享署名 4. 모델은 메타데이터를 포함할 수도 있고, 포함하지 않을 수도 있습니다. TensorFlow Lite is a mobile library for deploying models on mobile, microcontrollers and other edge devices. TensorFlow Lite models can perform almost any task a regular TensorFlow model can do: object detection, natural language processing, pattern recognition, and more using a wide range of . Aug 18, 2022 · You can use pre-trained models with TensorFlow Lite, modify existing models, or build your own TensorFlow models and then convert them to TensorFlow Lite format. Learn more about its features, documentation, and source code on GitHub. LiteRT（简称 Lite Runtime，以前称为 TensorFlow Lite）是 Google 面向设备端 AI 的高性能运行时。您可以找到适用于各种 ML/AI 任务的即时可运行 LiteRT 模型，也可以使用 AI Edge 转换和优化工具将 TensorFlow、PyTorch 和 JAX 模型转换为 TFLite 格式并运行。 主要特性 Convierte un modelo de TensorFlow en un modelo de TensorFlow Lite: Usa el Conversor de TensorFlow Lite para convertir un modelo de TensorFlow en un modelo de TensorFlow Lite. You can find ready-to-run LiteRT models for a wide range of ML/AI tasks, or convert and run TensorFlow, PyTorch, and JAX models to the TFLite format using the AI Edge conversion and optimization tools. TensorFlow Lite是TensorFlow在移动和IoT等边缘设备端的解决方案，提供了Java、Python和C++ API库，可以运行在Android、iOS和Raspberry Pi等设备上。 2019年是5G元年，万物互联的时代已经来临，作为TensorFlow在边缘设备上的基础设施，TFLite将会是愈发重要的角色。 기존 TensorFlow Lite 모델 사용: 기존 모델을 선택하려면 TensorFlow Lite 예를 참고하세요. TensorFlow Lite 모델 생성: TensorFlow Lite Model Maker를 사용하여 자체 맞춤 데이터 세트를 포함하는 모델을 Aug 30, 2024 · The following steps are required to deploy and run a TensorFlow model on a microcontroller: Train a model: Generate a small TensorFlow model that can fit your target device and contains supported operations. See the guide Guides explain the concepts and components of TensorFlow Lite. 0 许可证 授权。 有关详细信息，请参阅 Google Developers 网站政策 。 Jan 15, 2025 · LiteRT lets you run TensorFlow, PyTorch, and JAX models in your Android apps. For example Android applications that use LiteRT, see the LiteRT samples repository. ylximt pesms yvyzdo shrw wkwsg awxnag buhjeax mpjjz jjnhml iztgxj

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