Ampere® optimized build of
llama.cpp with full support for rich collection of GGUF models available at HuggingFace:
GGUF models
This Docker image can be run on bare metal Ampere® CPUs and Ampere® based VMs available in the cloud.
Release notes and binary executables are available on our
GitHub
Default entrypoint runs the server binary of llama.cpp, mimicking behavior of original llama.cpp server image:
docker image
Ampere® optimized build of llama.cpp provides support for two new quantization methods, Q4_K_4 and Q8R16, offering model size and perplexity similar to Q4_K and Q8_0, respectively, but performing up to 1.5-2x faster on inference.
First, you'll need to convert the model to the GGUF format using
this script:
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