8000 docs: LLAMA_CUBLAS -> LLAMA_CUDA · coderonion/llama-cpp-python@c50309e · GitHub
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docs: LLAMA_CUBLAS -> LLAMA_CUDA
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README.md

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@@ -102,10 +102,10 @@ CMAKE_ARGS="-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" pip install llama-cpp-
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<details>
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<summary>cuBLAS (CUDA)</summary>
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To install with cuBLAS, set the `LLAMA_CUBLAS=on` environment variable before installing:
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To install with cuBLAS, set the `LLAMA_CUDA=on` environment variable before installing:
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```bash
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CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python
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CMAKE_ARGS="-DLLAMA_CUDA=on" pip install llama-cpp-python
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```
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</details>
@@ -569,7 +569,7 @@ python3 -m llama_cpp.server --model models/7B/llama-model.gguf
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Similar to Hardware Acceleration section above, you can also install with GPU (cuBLAS) support like this:
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```bash
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CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install 'llama-cpp-python[server]'
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CMAKE_ARGS="-DLLAMA_CUDA=on" FORCE_CMAKE=1 pip install 'llama-cpp-python[server]'
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python3 -m llama_cpp.server --model models/7B/llama-model.gguf --n_gpu_layers 35
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```
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