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/xcframework.md from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.01 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/docs/xcframework.md
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/docs/xcframework.md
-
curl -L -o xcframework.md https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/docs/xcframework.md
1.01 kB
| # XCFramework | |
| The XCFramework is a precompiled version of the library for iOS, visionOS, tvOS, | |
| and macOS. It can be used in Swift projects without the need to compile the | |
| library from source. For example: | |
| ```swift | |
| // swift-tools-version: 5.10 | |
| // The swift-tools-version declares the minimum version of Swift required to build this package. | |
| import PackageDescription | |
| let package = Package( | |
| name: "MyLlamaPackage", | |
| targets: [ | |
| .executableTarget( | |
| name: "MyLlamaPackage", | |
| dependencies: [ | |
| "LlamaFramework" | |
| ]), | |
| .binaryTarget( | |
| name: "LlamaFramework", | |
| url: "https://github.com/ggml-org/llama.cpp/releases/download/b5046/llama-b5046-xcframework.zip", | |
| checksum: "c19be78b5f00d8d29a25da41042cb7afa094cbf6280a225abe614b03b20029ab" | |
| ) | |
| ] | |
| ) | |
| ``` | |
| The above example is using an intermediate build `b5046` of the library. This can be modified | |
| to use a different version by changing the URL and checksum. | |