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authorJudd <foldl@users.noreply.github.com>2023-04-13 21:43:22 +0800
committerGitHub <noreply@github.com>2023-04-13 16:43:22 +0300
commit4579af95e8e16910f6dbab0994917a5b3901f0cf (patch)
tree030064ef6454a9a7f76591cea5e2d71c26d218c2 /README.md
parent8c3ffc2f048a372639906fb30ec3c2070288d3be (diff)
zig : update build.zig (#872)
* update * update readme * minimize the changes. --------- Co-authored-by: zjli2019 <zhengji.li@ingchips.com>
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@@ -149,21 +149,43 @@ https://user-images.githubusercontent.com/1991296/224442907-7693d4be-acaa-4e01-8
## Usage
-Here are the step for the LLaMA-7B model:
+Here are the step for the LLaMA-7B model.
+
+### Get the Code
```bash
-# build this repo
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
-make
+```
+
+### Build
+
+Note: For Windows, CMake or Zig can be used.
+
+1. Use `make`
+
+ ```bash
+ make
+ ```
-#For Windows and CMake, use the following command instead:
-cd <path_to_llama_folder>
-mkdir build
-cd build
-cmake ..
-cmake --build . --config Release
+1. Use CMake
+ ```bash
+ mkdir build
+ cd build
+ cmake ..
+ cmake --build . --config Release
+ ```
+
+1. Use Zig
+
+ ```bash
+ zig build -Drelease-fast
+ ```
+
+### Prepare Data & Run
+
+```bash
# obtain the original LLaMA model weights and place them in ./models
ls ./models
65B 30B 13B 7B tokenizer_checklist.chk tokenizer.model