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
File size: 1,429 Bytes
c59fd93 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | #!/usr/bin/env bash
set -e
# Parse command line arguments
MMPROJ=""
DEBUG=""
while [[ $# -gt 0 ]]; do
case $1 in
--mmproj)
MMPROJ="--mmproj"
shift
;;
--debug)
DEBUG="1"
shift
;;
*)
shift
;;
esac
done
MODEL_NAME="${MODEL_NAME:-$(basename "$MODEL_PATH")}"
OUTPUT_DIR="${OUTPUT_DIR:-../../models}"
TYPE="${OUTTYPE:-f16}"
METADATA_OVERRIDE="${METADATA_OVERRIDE:-}"
if [[ -n "$MMPROJ" ]]; then
CONVERTED_MODEL="${OUTPUT_DIR}/mmproj-${MODEL_NAME}.gguf"
else
CONVERTED_MODEL="${OUTPUT_DIR}/${MODEL_NAME}.gguf"
fi
echo "Model path: ${MODEL_PATH}"
echo "Model name: ${MODEL_NAME}"
echo "Data type: ${TYPE}"
echo "Converted model path:: ${CONVERTED_MODEL}"
echo "Metadata override: ${METADATA_OVERRIDE}"
if [[ -n "$DEBUG" ]]; then
CMD_ARGS=("python" "-m" "pdb")
else
CMD_ARGS=("python")
fi
CMD_ARGS+=("../../convert_hf_to_gguf.py" "--verbose")
CMD_ARGS+=("${MODEL_PATH}")
CMD_ARGS+=("--outfile" "${CONVERTED_MODEL}")
CMD_ARGS+=("--outtype" "${TYPE}")
CMD_ARGS+=("--model-name" "${MODEL_NAME}")
[[ -n "$METADATA_OVERRIDE" ]] && CMD_ARGS+=("--metadata" "${METADATA_OVERRIDE}")
[[ -n "$MMPROJ" ]] && CMD_ARGS+=("${MMPROJ}")
"${CMD_ARGS[@]}"
echo ""
echo "The environment variable CONVERTED_MODEL can be set to this path using:"
echo "export CONVERTED_MODEL=$(realpath ${CONVERTED_MODEL})"
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