Text Classification
GGUF
jev-style
English
jev
openjev
decision-model
typed-decisions
bonsai
ternary
local-inference
blackwell
conversational
Instructions to use ajh-code/Jev-Bonsai-Compass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- jev-style
How to use ajh-code/Jev-Bonsai-Compass with jev-style:
pip install jev-style # GGUF builds score through llama.cpp: build the jev-score binary once hf download ajh-code/Jev-Bonsai-Compass build_jev_score.sh jev_score.cpp --local-dir jev-score export JEV_SCORE_BIN=$(sh jev-score/build_jev_score.sh /path/to/llama.cpp | tail -n 1)
from jev_style import JevStyle, noul, choice js = JevStyle.from_pretrained("ajh-code/Jev-Bonsai-Compass") out = js.decide("I was charged twice for one order.", { "billing": noul("This message is about billing."), "team": choice("Which team should handle it?", ["billing", "shipping", "tech"]), }) print(out["answers"]["team"]["choice"]) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ajh-code/Jev-Bonsai-Compass 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 ajh-code/Jev-Bonsai-Compass:Q2_0 # Run inference directly in the terminal: llama cli -hf ajh-code/Jev-Bonsai-Compass:Q2_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ajh-code/Jev-Bonsai-Compass:Q2_0 # Run inference directly in the terminal: llama cli -hf ajh-code/Jev-Bonsai-Compass:Q2_0
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 ajh-code/Jev-Bonsai-Compass:Q2_0 # Run inference directly in the terminal: ./llama-cli -hf ajh-code/Jev-Bonsai-Compass:Q2_0
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 ajh-code/Jev-Bonsai-Compass:Q2_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ajh-code/Jev-Bonsai-Compass:Q2_0
Use Docker
docker model run hf.co/ajh-code/Jev-Bonsai-Compass:Q2_0
- LM Studio
- Jan
- Ollama
How to use ajh-code/Jev-Bonsai-Compass with Ollama:
ollama run hf.co/ajh-code/Jev-Bonsai-Compass:Q2_0
- Unsloth Desktop
- Pi
How to use ajh-code/Jev-Bonsai-Compass with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ajh-code/Jev-Bonsai-Compass:Q2_0
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": "ajh-code/Jev-Bonsai-Compass:Q2_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use ajh-code/Jev-Bonsai-Compass with Docker Model Runner:
docker model run hf.co/ajh-code/Jev-Bonsai-Compass:Q2_0
- Lemonade
How to use ajh-code/Jev-Bonsai-Compass with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ajh-code/Jev-Bonsai-Compass:Q2_0
Run and chat with the model
lemonade run user.Jev-Bonsai-Compass-Q2_0
List all available models
lemonade list
- Hermes Agent
How to use ajh-code/Jev-Bonsai-Compass with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ajh-code/Jev-Bonsai-Compass:Q2_0
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 ajh-code/Jev-Bonsai-Compass:Q2_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use ajh-code/Jev-Bonsai-Compass with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ajh-code/Jev-Bonsai-Compass:Q2_0
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 "ajh-code/Jev-Bonsai-Compass:Q2_0" \ --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"
File size: 2,204 Bytes
b4b0f75 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | #!/usr/bin/env bash
set -euo pipefail
bundle_dir="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
mode="${1:-serve}"
if [[ "$mode" == serve || "$mode" == decide ]]; then
shift || true
else
mode=serve
fi
profile=current
args=("$@")
for ((i=0; i<${#args[@]}; i++)); do
if [[ "${args[$i]}" == --profile && $((i+1)) -lt ${#args[@]} ]]; then
profile="${args[$((i+1))]}"
fi
done
if [[ "$profile" != current && "$profile" != base ]]; then
echo 'Profile must be current or base' >&2
exit 2
fi
native="$bundle_dir/native/bin/llama-server"
model="$bundle_dir/models/Ternary-Bonsai-2-27B-PQ2_0.gguf"
adapter="$bundle_dir/adapters/broad-lr0.0001.adapter"
[[ -f "$native" && -f "$model" ]] || { echo 'Bundle is incomplete: native server or model missing' >&2; exit 2; }
# Some repository download clients materialize links as files or omit them.
ensure_link() {
local name="$1" target="$2"
if [[ ! -e "$bundle_dir/native/bin/$name" && ! -L "$bundle_dir/native/bin/$name" ]]; then
ln -s "$target" "$bundle_dir/native/bin/$name"
fi
}
for library in libggml-base libggml-cpu libggml-cuda libggml; do
ensure_link "$library.so.0" "$library.so.0.21.0"
ensure_link "$library.so" "$library.so.0"
done
for library in libllama-common libllama libmtmd; do
ensure_link "$library.so.0" "$library.so.0.2.0"
ensure_link "$library.so" "$library.so.0"
done
if [[ ! -x "$native" ]]; then
chmod u+x "$native" || { echo 'Native server needs executable permission' >&2; exit 2; }
fi
extra=()
if [[ "$profile" == current ]]; then
[[ -f "$adapter" ]] || { echo 'Bundle is incomplete: adapter missing' >&2; exit 2; }
extra+=(--adapter "$adapter")
fi
cd "$bundle_dir"
export PYTHONPATH="$bundle_dir/source${PYTHONPATH:+:$PYTHONPATH}"
export PYTHONDONTWRITEBYTECODE=1
python_bin="${BONSAI_PYTHON:-python3}"
if [[ "$mode" == decide ]]; then
exec "$python_bin" -c 'from bonsai_runtime.service import cli; cli()' \
--launch --profile "$profile" --model "$model" --binary "$native" "${extra[@]}" "${args[@]}"
fi
exec "$python_bin" -c 'from bonsai_runtime.service import http_cli; http_cli()' \
--launch --profile "$profile" --model "$model" --binary "$native" "${extra[@]}" "${args[@]}"
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