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 docs/install.md from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.83 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/docs/install.md
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/docs/install.md
-
curl -L -o install.md https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/docs/install.md
Install pre-built version of llama.cpp
| Install via | Windows | Mac | Linux |
|---|---|---|---|
| conda-forge | β | β | β |
| Winget | β | ||
| Homebrew | β | β | |
| MacPorts | β | ||
| Nix | β | β |
conda-forge (Windows, Mac and Linux)
conda-forge provides builds for:
- CUDA (Windows and Linux)
- Vulkan (Windows and Linux)
- Apple Metal (macOS)
conda install -c conda-forge llama.cpp
mamba install -c conda-forge llama.cpp
# Project-local installation
pixi add llama.cpp
# Global installation
pixi global install llama.cpp
This distribution is managed on conda-forge/llama.cpp-feedstock.
Shall you have any problems, please open an issue on its issue tracker.
Winget (Windows)
winget install llama.cpp
The package is automatically updated with new llama.cpp releases. More info: https://github.com/ggml-org/llama.cpp/issues/8188
Homebrew (Mac and Linux)
brew install llama.cpp
The formula is automatically updated with new llama.cpp releases. More info: https://github.com/ggml-org/llama.cpp/discussions/7668
MacPorts (Mac)
sudo port install llama.cpp
See also: https://ports.macports.org/port/llama.cpp/details/
Nix (Mac and Linux)
nix profile install nixpkgs#llama-cpp
For flake enabled installs.
Or
nix-env --file '<nixpkgs>' --install --attr llama-cpp
For non-flake enabled installs.
This expression is automatically updated within the nixpkgs repo.