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-msys.yml from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.98 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/.github/workflows/build-msys.yml
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/.github/workflows/build-msys.yml
-
curl -L -o build-msys.yml https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/.github/workflows/build-msys.yml
1.98 kB
| name: CI (msys) | |
| on: | |
| # only manual triggers due to low-importance of the workflows | |
| # TODO: for regular runs, provision dedicated self-hosted runners | |
| workflow_dispatch: | |
| # run once every week | |
| schedule: | |
| - cron: '0 0 * * 0' | |
| 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-msys2: | |
| runs-on: windows-2025 | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| include: | |
| - { sys: UCRT64, env: ucrt-x86_64, compiler: gcc, build: Release } | |
| - { sys: CLANG64, env: clang-x86_64, compiler: clang, build: Release } | |
| steps: | |
| - name: Clone | |
| uses: actions/checkout@v6 | |
| #- name: ccache | |
| # uses: ggml-org/ccache-action@v1.2.16 | |
| # with: | |
| # key: msys-windows-2025-x64 | |
| # variant: ccache | |
| # evict-old-files: 1d | |
| # save: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }} | |
| - name: Setup ${{ matrix.sys }} | |
| uses: msys2/setup-msys2@cafece8e6baf9247cf9b1bf95097b0b983cc558d # v2 | |
| with: | |
| update: true | |
| msystem: ${{matrix.sys}} | |
| install: >- | |
| mingw-w64-${{matrix.env}}-${{matrix.compiler}} | |
| mingw-w64-${{matrix.env}}-cmake | |
| mingw-w64-${{matrix.env}}-openblas | |
| - name: Build using CMake | |
| shell: msys2 {0} | |
| run: | | |
| cmake -B build | |
| cmake --build build --config ${{ matrix.build }} -j $(nproc) | |
| - name: Clean after building using CMake | |
| shell: msys2 {0} | |
| run: | | |
| rm -rf build | |
| - name: Build using CMake w/ OpenBLAS | |
| shell: msys2 {0} | |
| run: | | |
| cmake -B build -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS | |
| cmake --build build --config ${{ matrix.build }} -j $(nproc) | |