How to use Safeeq/FCtiny with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Safeeq/FCtiny # Run inference directly in the terminal: llama cli -hf Safeeq/FCtiny
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Safeeq/FCtiny # Run inference directly in the terminal: llama cli -hf Safeeq/FCtiny
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Safeeq/FCtiny # Run inference directly in the terminal: ./llama-cli -hf Safeeq/FCtiny
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Safeeq/FCtiny # Run inference directly in the terminal: ./build/bin/llama-cli -hf Safeeq/FCtiny
docker model run hf.co/Safeeq/FCtiny
How to use Safeeq/FCtiny with vLLM:
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Safeeq/FCtiny" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Safeeq/FCtiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'
How to use Safeeq/FCtiny with Ollama:
ollama run hf.co/Safeeq/FCtiny
How to use Safeeq/FCtiny with Docker Model Runner:
How to use Safeeq/FCtiny with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Safeeq/FCtiny
lemonade run user.FCtiny-{{QUANT_TAG}}
lemonade list
