Image-Text-to-Text
MLX
Safetensors
English
Polish
multilingual
gemma4
apple-silicon
gemma
gemma-4
abliterated
uncensored
Mixture of Experts
multimodal
vision
vmlx
nvfp4
4bit
quantized
huihui
conversational
4-bit precision
Instructions to use LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4 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("LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4") config = load_config("LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4") # 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
- LM Studio
- Pi new
How to use LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4"
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": "LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4 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 "LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4"
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 LibraxisAI/Huihui4-48B-A4B-vmlx-nvfp4
Run Hermes
hermes
card: add 'Inference tested on' link to mlx-batch-server
Browse files
README.md
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- **Apple MLX team** β MLX framework, quantization primitives.
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- **`Blaizzy/mlx-vlm`** β upstream multimodal MLX runtime; this build uses our editable LibraxisAI delta which we are upstreaming as separate PRs.
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---
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`π
ππππππππππ. with AI Agents by VetCoders (c)2024-2026 The LibraxisAI Team`
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- **Apple MLX team** β MLX framework, quantization primitives.
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- **`Blaizzy/mlx-vlm`** β upstream multimodal MLX runtime; this build uses our editable LibraxisAI delta which we are upstreaming as separate PRs.
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## Inference tested on
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[`LibraxisAI/mlx-batch-server`](https://github.com/LibraxisAI/mlx-batch-server)
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---
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`π
ππππππππππ. with AI Agents by VetCoders (c)2024-2026 The LibraxisAI Team`
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