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Tiny LLM

TriForce edited this page May 30, 2024 · 4 revisions

Original post by Ordinary_Tension5730

Hello,
Today, I managed to get the llama2.c project running on my powkiddy v90 with the miyoo cfw. If anyone wants to give it a go, let's go.

First of all, I wanted to thank Apaczer from the git MiyooCFW for providing me with some useful links. To start with, you need to be on a Linux distribution, personally, I'm on a debian bookworm. Then you need to download the external toolchain or compile it.

For beginners I advise you to use the following link: https://github.com/MiyooCFW/toolchain/releases

And download the already compiled tar.gz and decompress it in the /opt/miyoo folder with a tar -xvf Once the toolchain has been extracted, you need to download the git llama2.c using the following command:

git clone https://github.com/karpathy/llama2.c.git in the /opt folder

If you've succeeded, you now have a llama2.c folder in the /opt folder. Now you need to compile the run.c file using the external toolchain.
You should use a command like :

./arm-buildroot-linux-musleabi-gcc -Ofast -march=armv5te -o /opt/run /opt/llama2.c/run.c -lm -funroll-all-loops

In order to find the gcc for arm you have to search in the toolchain in the bin folder (/opt/miyoo/arm-buildroot-linux-musleabi_sdk-buildroot/bin).
If you get this error:

error: unknown type name 'int8_t'; did you mean 'intptr_t'?

You need to add this line to the run.c file in llama2.c folder

include <stdint.h>

You should now have a file called run in the /opt folder. All that's left to do is add it to the rest of the llama2.c folder and add the whole llama2.c folder to your console. Personally, I put it in the script folder I created for the occasion. Final step to do is download one of the test models found on this page in the models section:

https://github.com/karpathy/llama2.c

Start by testing with the 260K which is mediocre in result but has good performance to see if everything is fine. You need to add the models to the llama2.c folder in the console and run the script. Here are some images of the two smallest models.

image

Sources:

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