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
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Download examples/simple/README.md from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 912 Bytes
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/examples/simple/README.md
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/examples/simple/README.md
-
curl -L -o README.md https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/examples/simple/README.md
912 Bytes
| # llama.cpp/example/simple | |
| The purpose of this example is to demonstrate a minimal usage of llama.cpp for generating text with a given prompt. | |
| ```bash | |
| ./llama-simple -m ./models/llama-7b-v2/ggml-model-f16.gguf "Hello my name is" | |
| ... | |
| main: n_len = 32, n_ctx = 2048, n_parallel = 1, n_kv_req = 32 | |
| Hello my name is Shawn and I'm a 20 year old male from the United States. I'm a 20 year old | |
| main: decoded 27 tokens in 2.31 s, speed: 11.68 t/s | |
| llama_print_timings: load time = 579.15 ms | |
| llama_print_timings: sample time = 0.72 ms / 28 runs ( 0.03 ms per token, 38888.89 tokens per second) | |
| llama_print_timings: prompt eval time = 655.63 ms / 10 tokens ( 65.56 ms per token, 15.25 tokens per second) | |
| llama_print_timings: eval time = 2180.97 ms / 27 runs ( 80.78 ms per token, 12.38 tokens per second) | |
| llama_print_timings: total time = 2891.13 ms | |
| ``` | |