The first step is to specify which APIs our application needs. This is done using an IDL called WIT. For our example, we need the Console API. We can import it by specifying the name of the interface.
该流程首先使用 TRL/SFTTrainer 对 JSONL 格式的训练数据上的 google/functiongemma-270m-it 基础模型进行微调。训练完成后，使用 ai-edge-torch 和 dynamic_int8 量化算法将模型转换为 TFLite 格式。最后一步取决于目标运行时环境：对于 MediaPipe，将 TFLite 模型与分词器和停止标记合并到一个 .task 包中，该包可在 iOS、Android 和 Web 上运行。或者，你可以将其打包为 .litertlm 格式，用于 LiteRT-LM 运行时，该运行时提供 NPU 加速和更广泛的平台支持，包括桌面平台。
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