Instructions to use Hal0ai/hal0-brain-sft-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hal0ai/hal0-brain-sft-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Hal0ai/hal0-brain-sft-GGUF",
	filename="model.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Hal0ai/hal0-brain-sft-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 Hal0ai/hal0-brain-sft-GGUF
# Run inference directly in the terminal:
llama cli -hf Hal0ai/hal0-brain-sft-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Hal0ai/hal0-brain-sft-GGUF
# Run inference directly in the terminal:
llama cli -hf Hal0ai/hal0-brain-sft-GGUF

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 Hal0ai/hal0-brain-sft-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Hal0ai/hal0-brain-sft-GGUF

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 Hal0ai/hal0-brain-sft-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Hal0ai/hal0-brain-sft-GGUF

Use Docker

docker model run hf.co/Hal0ai/hal0-brain-sft-GGUF

LM Studio
Jan

vLLM

How to use Hal0ai/hal0-brain-sft-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Hal0ai/hal0-brain-sft-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": "Hal0ai/hal0-brain-sft-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Hal0ai/hal0-brain-sft-GGUF

Ollama
How to use Hal0ai/hal0-brain-sft-GGUF with Ollama:
```
ollama run hf.co/Hal0ai/hal0-brain-sft-GGUF
```

Unsloth Studio

How to use Hal0ai/hal0-brain-sft-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 Hal0ai/hal0-brain-sft-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 Hal0ai/hal0-brain-sft-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Hal0ai/hal0-brain-sft-GGUF to start chatting

How to use Hal0ai/hal0-brain-sft-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Hal0ai/hal0-brain-sft-GGUF

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": "Hal0ai/hal0-brain-sft-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Hal0ai/hal0-brain-sft-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 Hal0ai/hal0-brain-sft-GGUF

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 Hal0ai/hal0-brain-sft-GGUF

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use Hal0ai/hal0-brain-sft-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Hal0ai/hal0-brain-sft-GGUF

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 "Hal0ai/hal0-brain-sft-GGUF" \
  --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"

Docker Model Runner
How to use Hal0ai/hal0-brain-sft-GGUF with Docker Model Runner:
```
docker model run hf.co/Hal0ai/hal0-brain-sft-GGUF
```

Lemonade

How to use Hal0ai/hal0-brain-sft-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Hal0ai/hal0-brain-sft-GGUF

Run and chat with the model

lemonade run user.hal0-brain-sft-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

hal0-brain-sft (GGUF F16)

Single-file F16 GGUF of Hal0ai/hal0-brain-sft for llama.cpp / hal0-slot / Ollama users.

Same weights as the safetensors repo, repackaged as a GGUF for toolchains that can't consume HF transformers directly. Quant label in the GGUF general.file_type header is Q4_1 (the rocmfp4-llama fork's universal default — not to be trusted), but the actual weight tensors are F16. Match the 2.0 GB file size to confirm.

How hal0 uses this file

This is the brain slot's recommended load in installer/etc-hal0/slots/brain.toml:

[model]
default = "hal0-brain-sft"        # operator assigns one of the hal0ai/ GGUF variants
context_size = 65536

After hal0 model assign hal0-brain-sft-GGUF --slot brain && hal0 slot load brain, the GGUF is loaded by hal0-slot@brain.service (port 8089, GPU-Vulkan llama-server container, profile chat) and fronts the hal0/brain virtual model.

The brain is provisioned by hal0 API lifespan (ensure_brain_provisioned in src/hal0/brain/provision.py) and drives the shared toolloop.engine.run_tool_loop to serve /api/brain/chat (and the legacy /api/board/chat alias). Tool turns are routed off-slot to hal0/code or hal0/agent per [brain_chat].tool_model.

Usage — llama.cpp directly

# CLI
llama-cli -m model.gguf -p "What does the hal0 'agent' slot default to?" -n 256 --jinja

# Server (OpenAI-compatible, what hal0-slot wraps)
llama-server -m model.gguf --jinja -fa --port 8080

Usage — Ollama

# From a Modelfile
FROM ./model.gguf
PARAMETER stop "<|im_end|>"

ollama run hal0-brain-sft "What does the hal0 'agent' slot default to?"

Usage — hal0-slot (the official wiring)

# 1. Pull into hal0's local model store
hal0 model pull Hal0ai/hal0-brain-sft-GGUF

# 2. Assign to the brain slot (default port 8089, GPU-Vulkan)
hal0 model assign hal0-brain-sft --slot brain

# 3. Start the slot container
hal0 slot load brain

# 4. Verify it's serving
curl http://127.0.0.1:8089/v1/models

Then in hal0.toml:

[brain_chat]
enabled = true
model = "hal0/brain"
tool_model = "hal0/agent"          # OR "hal0/code" — routes tool turns
max_rounds = 8
completion_timeout_s = 300.0

Model details


Base model	`Hal0ai/hal0-brain-sft` (BF16 safetensors)
Relation	quantized (same weights, GGUF container)
Architecture	LlamaForCausalLM, 1.5B params
Dtype / quant	F16 (tensors)
SHA-256	`ed9d28c4eac1d7c291bc80d9410c243a3d28e655921ccaf90f2b6619aa24d2c3`
File size	2.0 GB
License	Apache-2.0

Hal0ai/hal0-brain-sft — BF16 safetensors (HF transformers)
Hal0ai/hal0-brain-sft-fpx8-agent — Q8_0 GGUF (agent slot)
Hal0ai/hal0-brain-sft-fpx4-agent — ROCmFP4 GGUF (AMD Strix)
Collection: hal0-brain

License

Apache-2.0.

Provenance

Repo: Hal0ai/hal0-brain-sft-GGUF
Org: Hal0ai
Project: https://github.com/Hal0ai/hal0
Brain spec: docs/rework/hal0-specs/spec-p3-brain.final.md

Downloads last month: 77

GGUF

Model size

1B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Model tree for Hal0ai/hal0-brain-sft-GGUF

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hal0-brain-sft-GGUF

hal0-brain-sft (GGUF F16)

How hal0 uses this file

Usage — llama.cpp directly

Usage — Ollama

Usage — hal0-slot (the official wiring)

Model details

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