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 src/llama-io.h from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 812 Bytes
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/src/llama-io.h
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/src/llama-io.h
-
curl -L -o llama-io.h https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/src/llama-io.h
812 Bytes
| struct ggml_tensor; | |
| class llama_io_write_i { | |
| public: | |
| llama_io_write_i() = default; | |
| virtual ~llama_io_write_i() = default; | |
| virtual void write(const void * src, size_t size) = 0; | |
| virtual void write_tensor(ggml_tensor * tensor, size_t offset, size_t size) = 0; | |
| // bytes written so far | |
| virtual size_t n_bytes() = 0; | |
| void write_string(const std::string & str); | |
| }; | |
| class llama_io_read_i { | |
| public: | |
| llama_io_read_i() = default; | |
| virtual ~llama_io_read_i() = default; | |
| virtual void read(void * dst, size_t size) = 0; | |
| virtual void read_tensor(ggml_tensor * tensor, size_t offset, size_t size) = 0; | |
| // bytes read so far | |
| virtual size_t n_bytes() = 0; | |
| void read_string(std::string & str); | |
| }; | |