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 vendor/hash/hash.cpp from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 581 Bytes
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/vendor/hash/hash.cpp
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/vendor/hash/hash.cpp
-
curl -L -o hash.cpp https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/vendor/hash/hash.cpp
581 Bytes
| extern "C" { | |
| } | |
| static std::string to_hex(const unsigned char * digest, size_t len) { | |
| static const char hex[] = "0123456789abcdef"; | |
| std::string out; | |
| out.reserve(2*len); | |
| for (size_t i = 0; i < len; ++i) { | |
| out += hex[digest[i] >> 4]; | |
| out += hex[digest[i] & 0xf]; | |
| } | |
| return out; | |
| } | |
| std::string hash_sha256_hex(const void * data, size_t len) { | |
| unsigned char digest[SHA256_DIGEST_SIZE]; | |
| sha256_hash(digest, (const unsigned char *) data, len); | |
| return to_hex(digest, SHA256_DIGEST_SIZE); | |
| } | |