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llama.cpp
g1
gss-llp
enterprise-ai
business-ai
enterprise-architecture
business-processes
workflow-reasoning
api-reasoning
security-reasoning
data-validation
offline-ai
local-inference
llama-cpp
commercial-use
enterprise
conversational
Instructions to use gsstec/G1-360M_V18.2_PRODUCTION_F16 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 gsstec/G1-360M_V18.2_PRODUCTION_F16 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 gsstec/G1-360M_V18.2_PRODUCTION_F16:F16 # Run inference directly in the terminal: llama cli -hf gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gsstec/G1-360M_V18.2_PRODUCTION_F16:F16 # Run inference directly in the terminal: llama cli -hf gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
Use pre-built binary
# 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 gsstec/G1-360M_V18.2_PRODUCTION_F16:F16 # Run inference directly in the terminal: ./llama-cli -hf gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
Build from source code
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 gsstec/G1-360M_V18.2_PRODUCTION_F16:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
Use Docker
docker model run hf.co/gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
- LM Studio
- Jan
- vLLM
How to use gsstec/G1-360M_V18.2_PRODUCTION_F16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gsstec/G1-360M_V18.2_PRODUCTION_F16" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gsstec/G1-360M_V18.2_PRODUCTION_F16", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
- Ollama
How to use gsstec/G1-360M_V18.2_PRODUCTION_F16 with Ollama:
ollama run hf.co/gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
- Unsloth Desktop
- Docker Model Runner
How to use gsstec/G1-360M_V18.2_PRODUCTION_F16 with Docker Model Runner:
docker model run hf.co/gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
- Lemonade
How to use gsstec/G1-360M_V18.2_PRODUCTION_F16 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gsstec/G1-360M_V18.2_PRODUCTION_F16:F16
Run and chat with the model
lemonade run user.G1-360M_V18.2_PRODUCTION_F16-F16
List all available models
lemonade list
- Atomic Chat

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- a7b0e7e376a8ab2c5802e3507daca01b7ac78cbdf65b30d32865f5e9d2239a55
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