Instructions to use pipenetwork/Holo-3.1-4B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use pipenetwork/Holo-3.1-4B-MLX-4bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("pipenetwork/Holo-3.1-4B-MLX-4bit") config = load_config("pipenetwork/Holo-3.1-4B-MLX-4bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use pipenetwork/Holo-3.1-4B-MLX-4bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "pipenetwork/Holo-3.1-4B-MLX-4bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "pipenetwork/Holo-3.1-4B-MLX-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use pipenetwork/Holo-3.1-4B-MLX-4bit with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "pipenetwork/Holo-3.1-4B-MLX-4bit"
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 pipenetwork/Holo-3.1-4B-MLX-4bit
Run Hermes
hermes
Holo-3.1-4B-MLX-4bit
4-bit MLX quantization of Hcompany/Holo-3.1-4B — H Company's
4B vision-language computer-use agent (UI grounding, mobile/desktop/web
automation), built on Qwen3.5-VL. Converted with mlx-vlm for Apple Silicon and
vision-validated (correctly grounded UI buttons + read on-screen text in testing).
Other quantizations: 4-bit (this) · 8-bit
📚 Part of the Holo-3.1 MLX (computer-use) collection.
| Precision | MLX 4-bit (LM quantized; vision tower kept in higher precision) |
| Type | Vision-language (image-text-to-text) |
| License | Apache 2.0 |
Requirements
Needs mlx-vlm with Qwen3.5-VL support. Qwen3.5-VL landed on mlx-vlm main; the
qwen3_5_vision model-type currently needs a 1-line allow-list addition (fix pending upstream):
pip install -U "git+https://github.com/Blaizzy/mlx-vlm"
# in mlx_vlm/models/qwen3_vl/vision.py, add "qwen3_5_vision" and "qwen3_5_moe_vision"
# to the allowed model_type list (until the official fix lands).
Usage
python -m mlx_vlm.generate --model pipenetwork/Holo-3.1-4B-MLX-4bit \
--image screenshot.png --prompt "What buttons are on screen?" --max-tokens 200
Conversion
python -m mlx_vlm.convert --hf-path Hcompany/Holo-3.1-4B --mlx-path <out> -q --q-bits 4 --q-group-size 64
Converted by pipenetwork with mlx-vlm. Original model Apache-2.0 by H Company; not affiliated.
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