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llamacpp-cuda-sm75
Dan13iel/llamacpp-cuda-sm75
llamacpp-cuda-sm75 is a machine learning model from Dan13iel. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Prebuilt llama-server / llama-cli from ggml-org/llama.cpp, compiled with -DGGMLCUDA=ON -DCMAKECUDAARCHITECTURES=75.
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Public
Updated Aug 30, 2026
Repo size
50.5 MB
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.gz50.5 MB · 100%
At a glance
- Access
- Public
- Created
- Aug 30, 2026
- Updated
- Aug 30, 2026
- SHA
- 4481f424
Model card
From the Hugging Face model README
llama.cpp CUDA build for Turing (SM75 / Tesla T4)
Prebuilt llama-server / llama-cli from ggml-org/llama.cpp,
compiled with -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=75.
llama.cpp publishes no Linux CUDA release binaries, and building from source on a 2-vCPU Colab box takes ~40 minutes. This tarball drops that to seconds.
- Build: b10690 (
0b5be7e) - Target: Turing only (SM 75) — Tesla T4, RTX 20xx, GTX 16xx
- Size: 50 MB. CUDA runtime + driver libs are not bundled; they link against
the host's
/usr/local/cudaand/usr/lib64-nvidia, which Colab and Kaggle images already provide.
Use
mkdir -p llamacpp-bin && curl -sL <file-url> | tar xz -C llamacpp-bin
export LD_LIBRARY_PATH=$PWD/llamacpp-bin:/usr/lib64-nvidia:/usr/local/cuda/targets/x86_64-linux/lib
./llamacpp-bin/llama-server --help
Upstream llama.cpp is MIT licensed; these are unmodified builds of it.
- Created
- Aug 30, 2026
- Updated
- Aug 30, 2026