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46 lines
1.4 KiB
Markdown
46 lines
1.4 KiB
Markdown
# llama.cpp
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llama.cpp is the best backend in two important scenarios:
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1) You don't have a GPU.
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2) You want to run a model that doesn't fit into your GPU.
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## Setting up the models
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#### Pre-converted
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Download the GGUF or GGML models directly into your `text-generation-webui/models` folder. It will be a single file.
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* For GGUF models, make sure its name contains `.gguf`.
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* For GGML models, make sure its name contains `ggml` and ends in `.bin`.
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`q4_K_M` quantization is recommended.
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#### Convert Llama yourself
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Follow the instructions in the llama.cpp README to generate a ggml: https://github.com/ggerganov/llama.cpp#prepare-data--run
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## GPU acceleration
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Enabled with the `--n-gpu-layers` parameter.
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* If you have enough VRAM, use a high number like `--n-gpu-layers 1000` to offload all layers to the GPU.
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* Otherwise, start with a low number like `--n-gpu-layers 10` and then gradually increase it until you run out of memory.
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This feature works out of the box for NVIDIA GPUs on Linux (amd64) or Windows. For other GPUs, you need to uninstall `llama-cpp-python` with
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```
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pip uninstall -y llama-cpp-python
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```
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and then recompile it using the commands here: https://pypi.org/project/llama-cpp-python/
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#### macOS
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For macOS, these are the commands:
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```
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pip uninstall -y llama-cpp-python
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CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install llama-cpp-python --no-cache-dir
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```
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