updated readme

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Concedo 2024-02-08 17:34:44 +08:00
parent f374dba49c
commit 22a4d84050

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@ -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.