Instructions to use apothic/bonsai-8B-1bit-turboquant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use apothic/bonsai-8B-1bit-turboquant 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 apothic/bonsai-8B-1bit-turboquant
# Run inference directly in the terminal:
llama cli -hf apothic/bonsai-8B-1bit-turboquant

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf apothic/bonsai-8B-1bit-turboquant
# Run inference directly in the terminal:
llama cli -hf apothic/bonsai-8B-1bit-turboquant

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 apothic/bonsai-8B-1bit-turboquant
# Run inference directly in the terminal:
./llama-cli -hf apothic/bonsai-8B-1bit-turboquant

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 apothic/bonsai-8B-1bit-turboquant
# Run inference directly in the terminal:
./build/bin/llama-cli -hf apothic/bonsai-8B-1bit-turboquant

Use Docker

docker model run hf.co/apothic/bonsai-8B-1bit-turboquant

LM Studio
Jan
Ollama
How to use apothic/bonsai-8B-1bit-turboquant with Ollama:
```
ollama run hf.co/apothic/bonsai-8B-1bit-turboquant
```

Unsloth Studio

How to use apothic/bonsai-8B-1bit-turboquant 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 apothic/bonsai-8B-1bit-turboquant 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 apothic/bonsai-8B-1bit-turboquant to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for apothic/bonsai-8B-1bit-turboquant to start chatting

How to use apothic/bonsai-8B-1bit-turboquant with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apothic/bonsai-8B-1bit-turboquant

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": "apothic/bonsai-8B-1bit-turboquant"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use apothic/bonsai-8B-1bit-turboquant with Docker Model Runner:
```
docker model run hf.co/apothic/bonsai-8B-1bit-turboquant
```

Lemonade

How to use apothic/bonsai-8B-1bit-turboquant with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull apothic/bonsai-8B-1bit-turboquant

Run and chat with the model

lemonade run user.bonsai-8B-1bit-turboquant-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use apothic/bonsai-8B-1bit-turboquant with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apothic/bonsai-8B-1bit-turboquant

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 apothic/bonsai-8B-1bit-turboquant

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use apothic/bonsai-8B-1bit-turboquant with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf apothic/bonsai-8B-1bit-turboquant

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 "apothic/bonsai-8B-1bit-turboquant" \
  --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"

bonsai-8B-1bit-turboquant / scripts /start_llama_server.sh

bitnom

Add Bonsai runtime scripts

2b4501a verified 5 months ago

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	#!/bin/sh
	# Start an OpenAI-compatible chat server with the Bonsai model.
	# Usage: ./scripts/start_llama_server.sh
	# Then open http://localhost:8080 in your browser.
	set -e

	SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
	. "$SCRIPT_DIR/common.sh"
	assert_valid_model
	DEMO_DIR="$(resolve_demo_dir)"
	cd "$DEMO_DIR"
	assert_gguf_downloaded

	HOST="0.0.0.0"
	PORT=8080
	: "${BONSAI_CACHE_TYPE_K:=f16}"
	: "${BONSAI_CACHE_TYPE_V:=f16}"

	# ── Check port is free ──
	if curl -s --max-time 2 "http://localhost:$PORT/health" >/dev/null 2>&1; then
	warn "llama-server is already running on port $PORT."
	echo " Stop it first with: kill \$(lsof -ti TCP:$PORT)"
	exit 1
	fi

	# ── Find model ──
	MODEL=""
	for _m in $GGUF_MODEL_DIR/*.gguf; do
	[ -f "$_m" ] && MODEL="$DEMO_DIR/$_m" && break
	done

	# ── Find binary ──
	BIN="$(find_llama_bin "$DEMO_DIR" llama-server \|\| true)"
	if [ -z "$BIN" ]; then
	err "llama-server not found. Build the cloned llama.cpp fork or set BONSAI_LLAMA_BIN_DIR."
	exit 1
	fi

	BIN_DIR="$(cd "$(dirname "$BIN")" && pwd)"
	export LD_LIBRARY_PATH="$BIN_DIR${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"

	echo ""
	echo "=== llama.cpp server (GGUF) ==="
	echo " Model: $(basename "$MODEL")"
	echo " Binary: $BIN"
	echo " Context: auto-fit (-c 0)"
	echo ""
	echo " Open http://localhost:$PORT in your browser to chat."
	echo " API: http://localhost:$PORT/v1/chat/completions"
	echo " Press Ctrl+C to stop."
	echo ""

	exec "$BIN" -m "$MODEL" --host "$HOST" --port "$PORT" -ngl 99 -c "$CTX_SIZE_DEFAULT" \
	--cache-type-k "$BONSAI_CACHE_TYPE_K" \
	--cache-type-v "$BONSAI_CACHE_TYPE_V" \
	--temp 0.5 --top-p 0.85 --top-k 20 --min-p 0 \
	--reasoning-budget 0 --reasoning-format none \
	--chat-template-kwargs '{"enable_thinking": false}' \
	"$@"