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 src/CMakeLists.txt from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.96 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/src/CMakeLists.txt
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/src/CMakeLists.txt
-
curl -L -o CMakeLists.txt https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/src/CMakeLists.txt
1.96 kB
| llama_add_compile_flags() | |
| # | |
| # libraries | |
| # | |
| # llama | |
| file(GLOB LLAMA_MODELS_SOURCES "models/*.cpp") | |
| add_library(llama | |
| ../include/llama.h | |
| llama.cpp | |
| llama-adapter.cpp | |
| llama-arch.cpp | |
| llama-batch.cpp | |
| llama-chat.cpp | |
| llama-context.cpp | |
| llama-cparams.cpp | |
| llama-grammar.cpp | |
| llama-graph.cpp | |
| llama-hparams.cpp | |
| llama-impl.cpp | |
| llama-io.cpp | |
| llama-kv-cache.cpp | |
| llama-kv-cache-iswa.cpp | |
| llama-kv-cache-dsa.cpp | |
| llama-kv-cache-dsa-iswa.cpp | |
| llama-kv-cache-msa.cpp | |
| llama-kv-cache-dsv4.cpp | |
| llama-memory.cpp | |
| llama-memory-hybrid.cpp | |
| llama-memory-hybrid-iswa.cpp | |
| llama-memory-hybrid-idx.cpp | |
| llama-memory-recurrent.cpp | |
| llama-mmap.cpp | |
| llama-model-loader.cpp | |
| llama-model-saver.cpp | |
| llama-model.cpp | |
| llama-quant.cpp | |
| llama-sampler.cpp | |
| llama-vocab.cpp | |
| unicode-data.cpp | |
| unicode.cpp | |
| unicode.h | |
| ${LLAMA_MODELS_SOURCES} | |
| ) | |
| set_target_properties(llama PROPERTIES | |
| VERSION ${LLAMA_VERSION_BASE} | |
| SOVERSION ${LLAMA_VERSION_MAJOR} | |
| MACHO_CURRENT_VERSION 0 # keep macOS linker from seeing oversized version number | |
| ) | |
| target_compile_definitions(llama PRIVATE | |
| LLAMA_VERSION="${LLAMA_VERSION}" | |
| LLAMA_COMMIT="${LLAMA_BUILD_COMMIT}" | |
| ) | |
| target_include_directories(llama PRIVATE .) | |
| target_include_directories(llama PUBLIC ../include) | |
| target_compile_features (llama PRIVATE cxx_std_17) # don't bump | |
| target_link_libraries(llama PUBLIC ggml) | |
| if (BUILD_SHARED_LIBS) | |
| set_target_properties(llama PROPERTIES POSITION_INDEPENDENT_CODE ON) | |
| target_compile_definitions(llama PRIVATE LLAMA_BUILD) | |
| target_compile_definitions(llama PUBLIC LLAMA_SHARED) | |
| endif() | |