# llama.cpp

llama.cpp is the best backend in two important scenarios:

1) You don't have a GPU.
2) You want to run a model that doesn't fit into your GPU.

## Setting up the models

#### Pre-converted

Download the ggml model directly into your `text-generation-webui/models` folder, making sure that its name contains `ggml` somewhere and ends in `.bin`. It's a single file.

`q4_K_M` quantization is recommended.

#### Convert Llama yourself

Follow the instructions in the llama.cpp README to generate a ggml: https://github.com/ggerganov/llama.cpp#prepare-data--run

## GPU acceleration

Enabled with the `--n-gpu-layers` parameter. 

* If you have enough VRAM, use a high number like `--n-gpu-layers 1000` to offload all layers to the GPU. 
* Otherwise, start with a low number like `--n-gpu-layers 10` and then gradually increase it until you run out of memory.

This feature works out of the box for NVIDIA GPUs. For other GPUs, you need to uninstall `llama-cpp-python` with

```
pip uninstall -y llama-cpp-python
```

and then recompile it using the commands here: https://pypi.org/project/llama-cpp-python/

#### macOS

For macOS, these are the commands:

```
pip uninstall -y llama-cpp-python
CMAKE_ARGS="-DLLAMA_METAL=on" FORCE_CMAKE=1 pip install llama-cpp-python --no-cache-dir
```