Image-Text-to-Text
MLX
Safetensors
qwen3_5
ornith
ornith-1.5
multimodal
abliterated
mlx-vlm
conversational
Instructions to use PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16 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("PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16") config = load_config("PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16") # 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 PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16 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 "PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16"
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 PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16 with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16"
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 "PocketAiHub/Ornith-1.5-9B-Abliterated-MLX-BF16" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 1,193 Bytes
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"schema_version": 1,
"method": "refusal-direction orthogonal weight projection",
"base_model": "ornith-ai/Ornith-1.5-9B",
"base_revision": "c927ad73b7eb20f00aafcaa0a11a9d58ed5487bc",
"direction": {
"examples_per_class": 256,
"kind": "projected_unit_directions",
"sha256": "97a251920007b644759f7492f0239322657bbb12920522e0a4be6d3852aadffb",
"source_layer": 23,
"hidden_state": "residual_post at the assistant-generation boundary"
},
"projection": {
"destination_layers": [
12,
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20,
21,
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],
"target_kinds": [
"full_attention_out",
"linear_attention_out",
"mlp_down"
],
"scale": 1.0,
"norm_preserve": true,
"modified_tensor_count": 40,
"modified_by_kind": {
"full_attention_out": 5,
"linear_attention_out": 15,
"mlp_down": 20
}
},
"architecture": {
"modelType": "qwen3_5",
"modelName": "Ornith-1.5-9B",
"hiddenSize": 4096,
"numHiddenLayers": 32,
"fullAttentionInterval": 4
}
}
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