Instructions to use prism-ml/Ternary-Bonsai-2-27B-gguf 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 prism-ml/Ternary-Bonsai-2-27B-gguf 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 prism-ml/Ternary-Bonsai-2-27B-gguf:F16 # Run inference directly in the terminal: llama cli -hf prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf prism-ml/Ternary-Bonsai-2-27B-gguf:F16 # Run inference directly in the terminal: llama cli -hf prism-ml/Ternary-Bonsai-2-27B-gguf: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 prism-ml/Ternary-Bonsai-2-27B-gguf:F16 # Run inference directly in the terminal: ./llama-cli -hf prism-ml/Ternary-Bonsai-2-27B-gguf: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 prism-ml/Ternary-Bonsai-2-27B-gguf:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Use Docker
docker model run hf.co/prism-ml/Ternary-Bonsai-2-27B-gguf:F16
- LM Studio
- Jan
- vLLM
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "prism-ml/Ternary-Bonsai-2-27B-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "prism-ml/Ternary-Bonsai-2-27B-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/prism-ml/Ternary-Bonsai-2-27B-gguf:F16
- Ollama
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with Ollama:
ollama run hf.co/prism-ml/Ternary-Bonsai-2-27B-gguf:F16
- Unsloth Desktop
- Pi
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "prism-ml/Ternary-Bonsai-2-27B-gguf:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with Docker Model Runner:
docker model run hf.co/prism-ml/Ternary-Bonsai-2-27B-gguf:F16
- Lemonade
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Run and chat with the model
lemonade run user.Ternary-Bonsai-2-27B-gguf-F16
List all available models
lemonade list
- Hermes Agent
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use prism-ml/Ternary-Bonsai-2-27B-gguf with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf prism-ml/Ternary-Bonsai-2-27B-gguf:F16
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "prism-ml/Ternary-Bonsai-2-27B-gguf:F16" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
LM Studio says no
π₯² Failed to load the model
Failed to load model.
error loading model: llama_model_loader: failed to load model from E:\lm-studio\prism-ml\Ternary-Bonsai-2-27B-gguf\Ternary-Bonsai-2-27B-PQ2_0.gguf
RTX 3090, Qwen 3.8-27B-IQ4_XS no probs and 50 tok/s
I built a precompiled PrismML llama.cpp runtime for LM Studio that works as a drop-in backend extension on Windows with NVIDIA CUDA, so you can run PrismML Bonsai models directly in LM Studio without compiling llama.cpp yourself. Works for Cuda 13.3 and Cuda 13.4. Maybe even for others aswell but hasn't been tested for more.
https://github.com/NOXZURE/llama.cpp-PrismML-Fork-LmStudio
Relatively easy to put in
No need to mega, etc. They have binary releases:
https://github.com/PrismML-Eng/llama.cpp/releases
I wonder why the releases tab was empty when I checked the repo? I thought that was weird too since I clearly remember them having binary releases. Must have been a bug. Wasted 20 minutes compiling lol