litert community/Qwen2.5 0.5B Instruct This model provides a few variants of Qwen/Qwen2.5 0.5B Instruct that are ready for deployment on Android using the LiteRT (fka TFLite) stack and MediaPipe LLM Inference API. Use the models Colab Disclaimer: The target deployment surface for the LiteRT models is Android/iOS/Web and the stack has been optimized for performance on these targets. Trying out the system in Colab is an easier way to familiarize yourself with the LiteRT stack, with the caveat that the performance (memory and latency) on Colab could be much worse than on a local device. Android Download and install the apk. Follow the instructions in the app. To build the demo app from source, please follow the instructions from the GitHub repository. Performance Android Note that all benchmark stats are from a Samsung S24 Ultra with 1280 KV cache size with multiple prefill signatures enabled. Backend Prefill (tokens/sec) Decode (tokens/sec) Time to first token (sec) Memory (RSS in MB) Model size (MB) fp32 (baseline) cpu 90.30 tk/s 16.71 tk/s 5.24 s 4,503 MB 1,898 MB dynamic int8 cpu 250.73 tk/s 29.97 tk/s 2.31 s 1,363 MB 521 MB Model Size: measured by the size of the .tflite flatbuff…
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