Enable CUDA on llama.cpp with LLM
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- Dominant language
- Python
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Description
Following the docs to install works perfectly on my machine with Debian and an Nvidia GPU(3060). All of the CUDA bits are working as I can train models and do inference with PyTorch and see that the GPU gets activated.
When following the docs to install llama.cpp with llm install llm-llama-cpp and llm install llama-cpp-python the version that is installed does not attempt to use the GPU.
According the the llama.cpp page if it is compiled from the source this can be enabled with:
make clean && LLAMA_CUBLAS=1 make -j
Any recommendations for how to modify the installed llama.cpp to leverage a GPU and still communicate via the llm project?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the installation path for llm-llama-cpp and llama-cpp-python, along with the project documentation describing their integration. Determine how a CUDA-enabled llama.cpp build could be installed while remaining usable through the llm command, and verify that GPU-backed inference communicates correctly with the project.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, cli
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100