Improve README.md for building in Termux on Android devices.

*Added directions to build with `make`, and simplified `OpenBlas` method. 

*Now it's more clear where to _move_ the models in Termux. 

*`llama.cpp` is diverse, so I added a Usage example for new users.

I left `CLBlast` instructions unchanged. I may try to clean it up in the future.

README.md

@@ -771,37 +771,42 @@ And after 4.45 hours, you will have the final perplexity.
 
 ### Android
 
-#### Building the Project using Android NDK
+#### Building the Project in Termux (F-Droid)
-You can easily run `llama.cpp` on Android device with [termux](https://termux.dev/).
+[Termux](https://termux.dev/) is an alternative method to run `llama.cpp` on Android devices.
 
-First, install the essential packages for termux:
+Ensure Termux is up to date and clone the repo:
 ```
-pkg install clang wget git cmake
+apt update && apt upgrade
-```
+$HOME
-Second, obtain the [Android NDK](https://developer.android.com/ndk) and then build with CMake:
+git clone https://github.com/ggerganov/llama.cpp
-```
-$ mkdir build-android
-$ cd build-android
-$ export NDK=<your_ndk_directory>
-$ cmake -DCMAKE_TOOLCHAIN_FILE=$NDK/build/cmake/android.toolchain.cmake -DANDROID_ABI=arm64-v8a -DANDROID_PLATFORM=android-23 -DCMAKE_C_FLAGS=-march=armv8.4a+dotprod ..
-$ make
-```
-Install [termux](https://termux.dev/) on your device and run `termux-setup-storage` to get access to your SD card.
-Finally, copy the `llama` binary and the model files to your device storage. Here is a demo of an interactive session running on Pixel 5 phone:
-
-https://user-images.githubusercontent.com/271616/225014776-1d567049-ad71-4ef2-b050-55b0b3b9274c.mp4
-
-#### Building the Project using Termux (F-Droid)
-Termux from F-Droid offers an alternative route to execute the project on an Android device. This method empowers you to construct the project right from within the terminal, negating the requirement for a rooted device or SD Card.
-
-Outlined below are the directives for installing the project using OpenBLAS and CLBlast. This combination is specifically designed to deliver peak performance on recent devices that feature a GPU.
-
-If you opt to utilize OpenBLAS, you'll need to install the corresponding package.
-```
-apt install libopenblas
 ```
 
-Subsequently, if you decide to incorporate CLBlast, you'll first need to install the requisite OpenCL packages:
+Build `llama.cpp`:
+```
+$HOME
+cd llama.cpp
+make
+```
+
+It's possible to include OpenBlas while building:
+````
+$HOME
+pkg install libopenblas
+cd llama.cpp
+cmake -B build -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
+cd build
+cmake --build . --config Release
+```
+
+Move your model to the $HOME directory, for example:
+```
+cd storage/downloads
+mv 7b-model.gguf ~/
+```
+
+Usage example:`./llama.cpp/main -m ~/7b-model.gguf --color -c 2048 --keep -1 -n -2 -b 10 -i -ins`
+
+Alternatively, to enable CLBlast then install the requisite OpenCL packages:
 ```
 apt install ocl-icd opencl-headers opencl-clhpp clinfo
 ```
@@ -830,9 +835,7 @@ export LD_LIBRARY_PATH=/vendor/lib64:$LD_LIBRARY_PATH
 
 (Note: some Android devices, like the Zenfone 8, need the following command instead - "export LD_LIBRARY_PATH=/system/vendor/lib64:$LD_LIBRARY_PATH". Source: https://www.reddit.com/r/termux/comments/kc3ynp/opencl_working_in_termux_more_in_comments/ )
 
-For easy and swift re-execution, consider documenting this final part in a .sh script file. This will enable you to rerun the process with minimal hassle.
+For easy and swift re-execution, consider documenting this final part in a .sh script file. This will allow you to run `./main (...)` with minimal hassle.
-
-Place your desired model into the `~/llama.cpp/models/` directory and execute the `./main (...)` script.
 
 ### Docker