From 585d7cc59ed9a1cd215dbfd7ce0b7dbfe8db2993 Mon Sep 17 00:00:00 2001 From: Chester Hu Date: Wed, 25 Sep 2024 11:00:26 -0700 Subject: [PATCH] Demo app android xnnpack quick-fix for the bookmark link (#5642) Summary: Pull Request resolved: https://github.com/pytorch/executorch/pull/5642 quick fix for the in page link Reviewed By: kirklandsign Differential Revision: D63400245 --- .../android/LlamaDemo/docs/delegates/xnnpack_README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/demo-apps/android/LlamaDemo/docs/delegates/xnnpack_README.md b/examples/demo-apps/android/LlamaDemo/docs/delegates/xnnpack_README.md index a457d0d46e2..93d9a41a13a 100644 --- a/examples/demo-apps/android/LlamaDemo/docs/delegates/xnnpack_README.md +++ b/examples/demo-apps/android/LlamaDemo/docs/delegates/xnnpack_README.md @@ -1,6 +1,6 @@ # Building ExecuTorch Android Demo App for Llama running XNNPack -**[UPDATE - 09/25]** We have added support for running [Llama 3.2 models](#for-llama-3.2-1b-and-3b-models) on the XNNPack backend. We currently support inference on their original data type (BFloat16). We have also added instructions to run [Llama Guard 1B models](#for-llama-guard-1b-models) on-device. +**[UPDATE - 09/25]** We have added support for running [Llama 3.2 models](#for-llama-32-1b-and-3b-models) on the XNNPack backend. We currently support inference on their original data type (BFloat16). We have also added instructions to run [Llama Guard 1B models](#for-llama-guard-1b-models) on-device. This tutorial covers the end to end workflow for building an android demo app using CPU on device via XNNPack framework. More specifically, it covers: