[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["没有我需要的信息","missingTheInformationINeed","thumb-down"],["太复杂/步骤太多","tooComplicatedTooManySteps","thumb-down"],["内容需要更新","outOfDate","thumb-down"],["翻译问题","translationIssue","thumb-down"],["示例/代码问题","samplesCodeIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-07-24。"],[],[],null,["# Supporting multiple frameworks with TFLite\n\nThe machine learning (ML) models you use with LiteRT can be trained\nusing JAX, PyTorch or TensorFlow and then converted to a TFLite flatbuffer\nformat.\n\nSee the following pages for more details:\n\n- [Converting from JAX](/edge/litert/models/convert_jax)\n- [Converting from PyTorch](/edge/litert/models/convert_pytorch)\n- [Converting from TensorFlow](/edge/litert/models/convert_tf)\n\nAn overview of the TFLite Converter which is an important component of\nsupporting different frameworks with TFLite is on [Model conversion\noverview](/edge/litert/models/convert)."]]