shipping-a-model-in-a-react-native-applisted

# Shipping a model in a React Native app Two runtimes cover React Native and Expo, and they do not take the same artifact. Picking between them is the first decision here, before any package gets installed, because reading the wrong runtime's docs for an hour is a common way to lose an afternoon. ## Which artifact shape this needs | You are holding | Package | What it eats | |---|---|---| | A `.pte` file, plus `tokenizer.json`, `tokenizer_config.json`, `config.json` | `react-native-executorch` | An ExecuTorch program | | A single `.gguf` file | `llama.rn` | GGUF, self-contained | These are two separate native modules with two separate build steps. There is no package that takes both. If a `.pte` file gets handed to `llama.rn`, or a `.gguf` file to `react-native-executorch`, it fails to load, full stop. **If what you are holding is neither of these,** a merged Hugging Face checkpoint (`config.json` + `model*.safetensors`) or a PEFT adapter directory (`adapter_config.json` + `adapter_model.safetensors`), it is not shippable into React Native as is. Run **inspecting-a-model-bundle** first to confirm which shape you actually have, then convert: - To `.pte`: `optimum-cli export executorch`, covered below and in `references/executorch-path.md`. - To GGUF: `convert_hf_to_gguf.py` then `llama-quantize`, covered below and in `references/llama-rn-path.md`. A PEFT adapter directory converts to neither format directly. Either merge it into its base model first and export from