Text Generation
GGUF
llama.cpp
conversational
1-bit
llama-cpp
cuda
metal
on-device
hybrid-attention
prismml
bonsai
Eval Results
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
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 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
- Llama new
- 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 Desktop
- 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 @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/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"
1-bit Bonsai-27B on a 6 GB GTX 1660 SUPER: 19 -> 56.6 tok/s (+198%) with a Q1_0 CUDA patch for llama.cpp
#29 opened 10 days ago
by
Jonydeperq
Deploying Bonsai-2-27B (1.58-bit Ternary) on Android via Termux: A Complete Guide
#28 opened 13 days ago
by
gui233
request: add model
โค๏ธ 1
1
#27 opened about 2 months ago
by
alei707
Do it with Qwen3.8 27B!!
๐ 1
3
#25 opened 2 months ago
by
MaxForce01
RTX 3060 12 GB: > 31 tok/s, bad agentic coding
2
#24 opened 2 months ago
by
d9k
Bonsai 3.8 27B?
๐ 15
#22 opened 3 months ago
by
elpirater312
creating Bonsai-35B will be better
๐ 1
#21 opened 3 months ago
by
aliman32
Full review
#20 opened 3 months ago
by
gdevenyi
VLLM serve is not working
3
#19 opened 3 months ago
by
codegood
่ฐข่ฐขไฝ
๐ฅ 1
#18 opened 3 months ago
by
shijiuweidu
LM Studio
๐ 1
6
#17 opened 3 months ago
by
Melektavus22
Error in tokenizer
1
#16 opened 3 months ago
by
Ragoon35
Severe Russian language degradation and English code-switching in Ternary Bonsai 27B
๐๐ 17
3
#14 opened 4 months ago
by
maxwelhelp
ุงูุชู ููู ุงููุณุงุฆู
1
#13 opened 4 months ago
by
elhaddadi
Ollama 500 error loading Bonsai-27B GGUF (dspark architecture)
โ๐ 3
4
#11 opened 4 months ago
by
amdeld
totaly garbage
2
#9 opened 4 months ago
by
Easinarafat77
Issue with using "raw" benchmark scores for intelligence density
๐ฅ 2
3
#7 opened 4 months ago
by
Green-Sky
dpark or MTP command line
8
#6 opened 4 months ago
by
PhilippeEiffel
smallest lossless model possible?
๐ 2
1
#5 opened 4 months ago
by
tokukarin
The Q1_0 is phenomenal
๐ง ๐ 2
7
#2 opened 4 months ago
by
spanspek
Thank you
โค๏ธ๐ 17
3
#1 opened 4 months ago
by
PZdev