Instructions to use inferencerlabs/Ornith-1.0-397B-MLX-Q9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use inferencerlabs/Ornith-1.0-397B-MLX-Q9 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("inferencerlabs/Ornith-1.0-397B-MLX-Q9") config = load_config("inferencerlabs/Ornith-1.0-397B-MLX-Q9") # 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 inferencerlabs/Ornith-1.0-397B-MLX-Q9 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "inferencerlabs/Ornith-1.0-397B-MLX-Q9"
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": "inferencerlabs/Ornith-1.0-397B-MLX-Q9" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use inferencerlabs/Ornith-1.0-397B-MLX-Q9 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 "inferencerlabs/Ornith-1.0-397B-MLX-Q9"
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 inferencerlabs/Ornith-1.0-397B-MLX-Q9
Run Hermes
hermes
Update README.md
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README.md
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# Ornith-1.0-397B
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See Ornith-1.0-397B in action: [demonstration videos](https://youtube.com/xcreate)
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#### Tested with an M3 Ultra 512 GiB using [Inferencer app v2.0.
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- Text Inference: ~25.3 tokens/s @ 1000 tokens ~415.4 GiB
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- Vision Inference: ~23.4 tokens/s ~416.2 GiB
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# Ornith-1.0-397B
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See Ornith-1.0-397B in action: [demonstration videos](https://youtube.com/xcreate)
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#### Tested with an M3 Ultra 512 GiB using [Inferencer app v2.0.7](https://inferencer.com)
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- Text Inference: ~25.3 tokens/s @ 1000 tokens ~415.4 GiB
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- Vision Inference: ~23.4 tokens/s ~416.2 GiB
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