Merge branch 'master' into mpi
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README.md
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README.md
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@ -734,7 +734,7 @@ export LD_LIBRARY_PATH=/vendor/lib64:$LD_LIBRARY_PATH
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For easy and swift re-execution, consider documenting this final part in a .sh script file. This will enable you to rerun the process with minimal hassle.
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Place your desired model into the `/llama.cpp/models/` directory and execute the `./main (...)` script.
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Place your desired model into the `~/llama.cpp/models/` directory and execute the `./main (...)` script.
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### Docker
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@ -770,6 +770,38 @@ or with a light image:
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docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:light -m /models/7B/ggml-model-q4_0.bin -p "Building a website can be done in 10 simple steps:" -n 512
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```
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### Docker With CUDA
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Assuming one has the [nvidia-container-toolkit](https://github.com/NVIDIA/nvidia-container-toolkit) properly installed on Linux, or is using a GPU enabled cloud, `cuBLAS` should be accessible inside the container.
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#### Building Locally
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```bash
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docker build -t local/llama.cpp:full-cuda -f .devops/full-cuda.Dockerfile .
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docker build -t local/llama.cpp:light-cuda -f .devops/main-cuda.Dockerfile .
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```
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You may want to pass in some different `ARGS`, depending on the CUDA environment supported by your container host, as well as the GPU architecture.
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The defaults are:
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- `CUDA_VERSION` set to `11.7.1`
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- `CUDA_DOCKER_ARCH` set to `all`
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The resulting images, are essentially the same as the non-CUDA images:
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1. `local/llama.cpp:full-cuda`: This image includes both the main executable file and the tools to convert LLaMA models into ggml and convert into 4-bit quantization.
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2. `local/llama.cpp:light-cuda`: This image only includes the main executable file.
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#### Usage
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After building locally, Usage is similar to the non-CUDA examples, but you'll need to add the `--gpus` flag. You will also want to use the `--n-gpu-layers` flag.
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```bash
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docker run --gpus all -v /path/to/models:/models local/llama.cpp:full-cuda --run -m /models/7B/ggml-model-q4_0.bin -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
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docker run --gpus all -v /path/to/models:/models local/llama.cpp:light-cuda -m /models/7B/ggml-model-q4_0.bin -p "Building a website can be done in 10 simple steps:" -n 512 --n-gpu-layers 1
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```
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### Contributing
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- Contributors can open PRs
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@ -790,5 +822,10 @@ docker run -v /path/to/models:/models ghcr.io/ggerganov/llama.cpp:light -m /mode
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### Docs
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- [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks)
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- [main](./examples/main/README.md)
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- [server](./examples/server/README.md)
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- [embd-input](./examples/embd-input/README.md)
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- [jeopardy](./examples/jeopardy/README.md)
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- [BLIS](./docs/BLIS.md)
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- [Performance troubleshooting](./docs/token_generation_performance_tips.md)
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- [GGML tips & tricks](https://github.com/ggerganov/llama.cpp/wiki/GGML-Tips-&-Tricks)
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