From 22a4d84050559c2db10834a7683d4c58166561dd Mon Sep 17 00:00:00 2001
From: Concedo <39025047+LostRuins@users.noreply.github.com>
Date: Thu, 8 Feb 2024 17:34:44 +0800
Subject: [PATCH] updated readme

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 8ea897d56..fe82dd749 100644
--- a/README.md
+++ b/README.md
@@ -58,7 +58,7 @@ when you can't use the precompiled binary directly, we provide an automated buil
   - For Arch Linux: Install `cblas` `openblas` and `clblast`.
   - For Debian: Install `libclblast-dev` and `libopenblas-dev`.
 - You can attempt a CuBLAS build with `LLAMA_CUBLAS=1`. You will need CUDA Toolkit installed. Some have also reported success with the CMake file, though that is more for windows.
-- For a full featured build, do `make LLAMA_OPENBLAS=1 LLAMA_CLBLAST=1 LLAMA_CUBLAS=1`
+- For a full featured build (all backends), do `make LLAMA_OPENBLAS=1 LLAMA_CLBLAST=1 LLAMA_CUBLAS=1 LLAMA_VULKAN=1`
 - After all binaries are built, you can run the python script with the command `koboldcpp.py [ggml_model.bin] [port]`
 
 - Note: Many OSX users have found that the using Accelerate is actually faster than OpenBLAS. To try, you may wish to run with `--noblas` and compare speeds.