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 .devops/nix/python-scripts.nix from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.3 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/.devops/nix/python-scripts.nix
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/.devops/nix/python-scripts.nix
-
curl -L -o python-scripts.nix https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/.devops/nix/python-scripts.nix
1.3 kB
| { | |
| lib, | |
| stdenv, | |
| buildPythonPackage, | |
| poetry-core, | |
| mkShell, | |
| python3Packages, | |
| gguf-py, | |
| }@inputs: | |
| let | |
| llama-python-deps = with python3Packages; [ | |
| numpy | |
| sentencepiece | |
| transformers | |
| protobuf | |
| torchWithoutCuda | |
| gguf-py | |
| tqdm | |
| # for scripts/compare-llama-bench.py | |
| gitpython | |
| tabulate | |
| # for examples/pydantic-models-to-grammar-examples.py | |
| docstring-parser | |
| pydantic | |
| ]; | |
| llama-python-test-deps = with python3Packages; [ | |
| # Server bench | |
| matplotlib | |
| # server tests | |
| openai | |
| pytest | |
| prometheus-client | |
| ]; | |
| in | |
| buildPythonPackage ({ | |
| pname = "llama-scripts"; | |
| version = "0.0.0"; | |
| pyproject = true; | |
| # NOTE: The files filtered out here are not visible in the build sandbox, neither | |
| # do they affect the output hash. They can be modified without triggering a rebuild. | |
| src = lib.cleanSourceWith { | |
| filter = | |
| name: type: | |
| let | |
| any = builtins.any (x: x); | |
| baseName = builtins.baseNameOf name; | |
| in | |
| any [ | |
| (lib.hasSuffix ".py" name) | |
| (baseName == "README.md") | |
| (baseName == "pyproject.toml") | |
| ]; | |
| src = lib.cleanSource ../../.; | |
| }; | |
| nativeBuildInputs = [ poetry-core ]; | |
| nativeCheckInputs = llama-python-test-deps; | |
| dependencies = llama-python-deps; | |
| }) | |