Instructions to use prism-ml/Bonsai-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/Bonsai-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/Bonsai-27B-gguf:F16 # Run inference directly in the terminal: llama cli -hf prism-ml/Bonsai-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/Bonsai-27B-gguf:F16 # Run inference directly in the terminal: llama cli -hf prism-ml/Bonsai-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/Bonsai-27B-gguf:F16 # Run inference directly in the terminal: ./llama-cli -hf prism-ml/Bonsai-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/Bonsai-27B-gguf:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf prism-ml/Bonsai-27B-gguf:F16
Use Docker
docker model run hf.co/prism-ml/Bonsai-27B-gguf:F16
- LM Studio
- Jan
- vLLM
How to use prism-ml/Bonsai-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/Bonsai-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/Bonsai-27B-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/prism-ml/Bonsai-27B-gguf:F16
- Ollama
How to use prism-ml/Bonsai-27B-gguf with Ollama:
ollama run hf.co/prism-ml/Bonsai-27B-gguf:F16
- Unsloth Studio
How to use prism-ml/Bonsai-27B-gguf with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for prism-ml/Bonsai-27B-gguf to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for prism-ml/Bonsai-27B-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for prism-ml/Bonsai-27B-gguf to start chatting
- Pi
How to use prism-ml/Bonsai-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/Bonsai-27B-gguf:F16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/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/Bonsai-27B-gguf:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use prism-ml/Bonsai-27B-gguf with Docker Model Runner:
docker model run hf.co/prism-ml/Bonsai-27B-gguf:F16
- Lemonade
How to use prism-ml/Bonsai-27B-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull prism-ml/Bonsai-27B-gguf:F16
Run and chat with the model
lemonade run user.Bonsai-27B-gguf-F16
List all available models
lemonade list
- Hermes Agent
How to use prism-ml/Bonsai-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/Bonsai-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/Bonsai-27B-gguf:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use prism-ml/Bonsai-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/Bonsai-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/Bonsai-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
LM Studio 0.4.20
Runtime Selections GGUF Vulkan llama.cpp (Windows) v2.27.1
🥲 Не удалось загрузить модель
Engine protocol runtime llama-server for W0J/scmAONB9UF10tMKJty/J exited before becoming healthy. exitCode=1, signal=null
hmm that might be issue with LM Studio. For Q1_0 for Bonsai-27B-gguf , the llama-server should work. Which gguf did you download?
Q4_1 (2.72Gb) and BF16(8.22Gb). Both options give an error.
If there is "dspark" in the name the names then they are not the language models themselves, they are draft models for speculative decoding using dspark method, those ggufs by themselves don't do anything and need to be run in a special way, they definitely won't work in LM Studio. Can check here if curious: https://github.com/PrismML-Eng/Bonsai-demo/blob/main/SPECULATIVE.md
For LM Studio need to download the Q1_0 for the LLM part (Bonsai-27B-Q1_0.gguf)
and for vision part either Bonsai-27B-mmproj-BF16.gguf or Bonsai-27B-mmproj-Q8_0.gguf.
Overall can refer too https://github.com/PrismML-Eng/Bonsai-demo/, even if not running the demo direclty has a lot of useful info on how to run the models.
Thank you. Both (Bonsai-27B-Q1_0.gguf, Bonsai-27B-mmproj-BF16.gguf) worked.
will this quantize be relased ? so we can quantize using this method ?
or is it only one off ?
right now ts 50/50 working !