[[["เข้าใจง่าย","easyToUnderstand","thumb-up"],["แก้ปัญหาของฉันได้","solvedMyProblem","thumb-up"],["อื่นๆ","otherUp","thumb-up"]],[["ไม่มีข้อมูลที่ฉันต้องการ","missingTheInformationINeed","thumb-down"],["ซับซ้อนเกินไป/มีหลายขั้นตอนมากเกินไป","tooComplicatedTooManySteps","thumb-down"],["ล้าสมัย","outOfDate","thumb-down"],["ปัญหาเกี่ยวกับการแปล","translationIssue","thumb-down"],["ตัวอย่าง/ปัญหาเกี่ยวกับโค้ด","samplesCodeIssue","thumb-down"],["อื่นๆ","otherDown","thumb-down"]],["อัปเดตล่าสุด 2025-07-24 UTC"],[],[],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)."]]
