Instructions to use VladHong/llama-cpp-K2-FAST2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use VladHong/llama-cpp-K2-FAST2 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: llama cli -hf VladHong/llama-cpp-K2-FAST2
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: llama cli -hf VladHong/llama-cpp-K2-FAST2
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: ./build/bin/llama cli -hf VladHong/llama-cpp-K2-FAST2
Use Docker
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
- Llama new
- LM Studio
- Jan
- Ollama
How to use VladHong/llama-cpp-K2-FAST2 with Ollama:
ollama run hf.co/VladHong/llama-cpp-K2-FAST2
- Unsloth Desktop
- Docker Model Runner
How to use VladHong/llama-cpp-K2-FAST2 with Docker Model Runner:
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
- Lemonade
How to use VladHong/llama-cpp-K2-FAST2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VladHong/llama-cpp-K2-FAST2
Run and chat with the model
lemonade run user.llama-cpp-K2-FAST2-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download .github/workflows/build-opencl.yml from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 2.77 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/.github/workflows/build-opencl.yml
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/.github/workflows/build-opencl.yml
-
curl -L -o build-opencl.yml https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/.github/workflows/build-opencl.yml
2.77 kB
| name: CI (opencl) | |
| on: | |
| workflow_dispatch: # allows manual triggering | |
| push: | |
| branches: | |
| - master | |
| paths: [ | |
| '.github/workflows/build-opencl.yml', | |
| '**/CMakeLists.txt', | |
| '**/.cmake', | |
| '**/*.h', | |
| '**/*.hpp', | |
| '**/*.c', | |
| '**/*.cpp', | |
| '**/*.cl' | |
| ] | |
| pull_request: | |
| types: [opened, synchronize, reopened] | |
| paths: [ | |
| '.github/workflows/build-opencl.yml', | |
| 'ggml/src/ggml-opencl/**' | |
| ] | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }} | |
| cancel-in-progress: true | |
| env: | |
| GGML_NLOOP: 3 | |
| GGML_N_THREADS: 1 | |
| LLAMA_ARG_LOG_COLORS: 1 | |
| LLAMA_ARG_LOG_PREFIX: 1 | |
| LLAMA_ARG_LOG_TIMESTAMPS: 1 | |
| jobs: | |
| windows-2025-opencl-adreno: | |
| runs-on: windows-2025 | |
| steps: | |
| - name: Clone | |
| id: checkout | |
| uses: actions/checkout@v6 | |
| - name: ccache | |
| uses: ggml-org/ccache-action@v1.2.21 | |
| with: | |
| key: opencl-windows-2025-x64 | |
| variant: ccache | |
| evict-old-files: 1d | |
| save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }} | |
| - name: Install Ninja | |
| id: install_ninja | |
| run: | | |
| choco install ninja | |
| - name: Install OpenCL Headers and Libs | |
| id: install_opencl | |
| run: | | |
| git clone https://github.com/KhronosGroup/OpenCL-Headers | |
| cd OpenCL-Headers | |
| cmake -B build ` | |
| -DBUILD_TESTING=OFF ` | |
| -DOPENCL_HEADERS_BUILD_TESTING=OFF ` | |
| -DOPENCL_HEADERS_BUILD_CXX_TESTS=OFF ` | |
| -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release" | |
| cmake --build build --target install | |
| git clone https://github.com/KhronosGroup/OpenCL-ICD-Loader | |
| cd OpenCL-ICD-Loader | |
| cmake -B build-arm64-release ` | |
| -A arm64 ` | |
| -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" ` | |
| -DCMAKE_INSTALL_PREFIX="$env:RUNNER_TEMP/opencl-arm64-release" | |
| cmake --build build-arm64-release --target install --config release | |
| - name: Build | |
| id: cmake_build | |
| run: | | |
| cmake -S . -B build -G "Ninja Multi-Config" -D CMAKE_TOOLCHAIN_FILE=cmake/arm64-windows-llvm.cmake -DCMAKE_PREFIX_PATH="$env:RUNNER_TEMP/opencl-arm64-release" -DGGML_OPENCL=ON -DGGML_OPENCL_USE_ADRENO_KERNELS=ON -DLLAMA_BUILD_BORINGSSL=ON | |
| cmake --build build --config Release -j ${env:NUMBER_OF_PROCESSORS} | |
| - name: ccache-clear | |
| uses: ./.github/actions/ccache-clear | |
| env: | |
| GH_TOKEN: ${{ github.token }} | |
| with: | |
| key: opencl-windows-2025-x64 | |
| older: 5m | |
| min: 1 | |
| dry-run: ${{ github.event_name != 'push' || github.ref != 'refs/heads/master' }} | |