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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/google-ai-edge/litert-samples.저장소 README를 불러오는 중…
수집된 skill 11개 중 11개를 표시합니다.
Measure a LiteRT .tflite model with `benchmark_model` on Developer Device Platform (DDP) lab phones through `litert benchmark --ddp`, or on the Mac you run it from, and turn the session into rows of the performance leaderboard under benchmark/leaderboard -…
원문 언어: 영어
Convert a Hugging Face LLM or vision-language model checkpoint into a .litertlm bundle that runs on the LiteRT-LM runtime with verified quality - classify the architecture against known runtime walls, pick the recipe family (dense, reasoning, hybrid SSM,…
원문 언어: 영어
Prove a converted or quantized LiteRT model on the actual device via the CompiledModel API - confirm GPU residency, compare device output against the source model, and diagnose device-only failures such as silent CPU fallback, whole-graph compile ceilings,…
원문 언어: 영어
Get the current local time, date and day of the week.
원문 언어: 영어
Say which models, backends and accelerators this app is running and how much memory it uses.
원문 언어: 영어
Creates an Android app that runs a .tflite model on the CPU or the GPU with the LiteRT CompiledModel API in Kotlin. Use this skill to build a new app around a vision, audio or embedding model, or to add on-device inference to an existing app - the dependency,…
원문 언어: 영어
Creates an Android app that runs an open text LLM on the device, on the CPU or the GPU, with the LiteRT-LM Kotlin API. Use this skill to build a new chat, summarization or extraction app with a .litertlm model from Hugging Face litert-community (Gemma, Qwen,…
원문 언어: 영어
Rapidly migrate an Android application from legacy TensorFlow Lite (TFLite) to the modern LiteRT CompiledModel API (2.x) in Open Source GitHub repositories, keeping the TensorFlow Lite Support Library as LiteRT Support (litert-support 2.3.0). Covers buffer…
원문 언어: 영어
Build a new Android app (Kotlin, Compose) around a verified LiteRT model using the CompiledModel API - the app architecture, the inference-layer lifecycle rules, model delivery, and the UI traps that masquerade as model bugs. Use when turning a converted and…
원문 언어: 영어
Convert a PyTorch or Hugging Face model into a LiteRT model that runs fully on the GPU via the CompiledModel API with verified-correct output, and lay it out as a model recipe. Use when converting a new model, or when a converted model is rejected by the GPU,…
원문 언어: 영어
Shrink a converted LiteRT model with ai-edge-quantizer (fp16 / int8 / int4) without losing accuracy, verifying parity against the float source after every step. Use when choosing a quantization recipe for a new model, when a quantized model fails to load,…
원문 언어: 영어
README를 불러오지 못했습니다. 아래의 저장소 Skill 목록은 계속 이용할 수 있습니다.