char-fork/llama.cpp
git clone https://git.t4t.associates/char-fork/llama.cpp
8300f1411
char/aliceai-t5-moe
files
| README-MUSA.md | 1.0 KiB |
| README.md | 1.3 KiB |
| run.sh | 28.1 KiB |
CI
This CI implements heavy-duty workflows that run on self-hosted runners. Typically the purpose of these workflows is to cover hardware configurations that are not available from Github-hosted runners and/or require more computational resource than normally available.
It is a good practice, before publishing changes to execute the full CI locally on your machine. For example:
mkdir tmp# CPU-only build bash ./ci/run.sh ./tmp/results ./tmp/mnt# with CUDA support GG_BUILD_CUDA =1bash ./ci/run.sh ./tmp/results ./tmp/mnt# with SYCL support source /opt/intel/oneapi/setvars.shGG_BUILD_SYCL =1bash ./ci/run.sh ./tmp/results ./tmp/mnt# with MUSA support GG_BUILD_MUSA =1bash ./ci/run.sh ./tmp/results ./tmp/mnt# etc.
Adding self-hosted runners
- Add a self-hosted
ggml-ciworkflow to [[.github/workflows/build.yml]] with an appropriate label - Request a runner token from
ggml-org(for example, via a comment in the PR or email) - Set-up a machine using the received token (docs)
- Optionally update ci/run.sh to build and run on the target platform by gating the implementation with a
GG_BUILD_...env