How to use VladHong/llama-cpp-K2-FAST2 with llama.cpp:
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
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
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
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
How to use VladHong/llama-cpp-K2-FAST2 with Ollama:
ollama run hf.co/VladHong/llama-cpp-K2-FAST2
How to use VladHong/llama-cpp-K2-FAST2 with Docker Model Runner:
How to use VladHong/llama-cpp-K2-FAST2 with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VladHong/llama-cpp-K2-FAST2
lemonade run user.llama-cpp-K2-FAST2-{{QUANT_TAG}}
lemonade list
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tests/peg-parser/simple-tokenize.h
hf download hf://VladHong/llama-cpp-K2-FAST2/tests/peg-parser/simple-tokenize.h
curl -L -o simple-tokenize.h https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tests/peg-parser/simple-tokenize.h
