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/llama-eval/README.md from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 662 Bytes
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/examples/llama-eval/README.md
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/examples/llama-eval/README.md
-
curl -L -o README.md https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/examples/llama-eval/README.md
662 Bytes
llama-eval
Simple evaluation tool for llama.cpp with support for multiple datasets.
For a full description, usage examples, and sample results, see:
Quick start
# Single server
python3 llama-eval.py \
--server http://localhost:8033 \
--model my-model \
--dataset gsm8k --n_cases 100 \
--grader-type regex --threads 32
# Multiple servers (comma-separated URLs and thread counts)
python3 llama-eval.py \
--server http://server1:8033,http://server2:8033 \
--server-name server1,server2 \
--threads 16,16 \
--dataset aime2025 --n_cases 240 \
--grader-type regex