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 scripts/git-bisect-run.sh from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 407 Bytes
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/scripts/git-bisect-run.sh
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/scripts/git-bisect-run.sh
-
curl -L -o git-bisect-run.sh https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/scripts/git-bisect-run.sh
407 Bytes
| cmake_args=() | |
| llama_results_args=() | |
| for arg in "${@}"; do | |
| if [[ "$arg" == -D* ]]; then | |
| cmake_args+=("$arg") | |
| else | |
| llama_results_args+=("$arg") | |
| fi | |
| done | |
| dir="build-bisect" | |
| rm -rf ${dir} > /dev/null | |
| cmake -B ${dir} -S . ${cmake_args} > /dev/null | |
| cmake --build ${dir} -t llama-results -j $(nproc) > /dev/null | |
| ${dir}/bin/llama-results "${llama_results_args[@]}" | |