Image-Text-to-Text
MLX
Safetensors
English
Spanish
Chinese
qwen3_5
vlm
vision
osirisbrain
apple-silicon
qwen3.5
conversational
4-bit precision
Instructions to use osirisbrain/OsirisCortex-v7-Censo-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use osirisbrain/OsirisCortex-v7-Censo-MLX 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("osirisbrain/OsirisCortex-v7-Censo-MLX") config = load_config("osirisbrain/OsirisCortex-v7-Censo-MLX") # 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 osirisbrain/OsirisCortex-v7-Censo-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "osirisbrain/OsirisCortex-v7-Censo-MLX"
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": "osirisbrain/OsirisCortex-v7-Censo-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use osirisbrain/OsirisCortex-v7-Censo-MLX 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 "osirisbrain/OsirisCortex-v7-Censo-MLX"
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 osirisbrain/OsirisCortex-v7-Censo-MLX
Run Hermes
hermes
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license: apache-2.0
language:
- en
- es
- zh
tags:
- mlx
- vlm
- vision
- osirisbrain
- apple-silicon
- qwen3.5
base_model: Qwen/Qwen3.5-9B
pipeline_tag: image-text-to-text
library_name: mlx
---
# OsirisCortex-v7-Censo-MLX
**Cortex v7 (Censored + Vision)** — Osiris's main reasoning + vision brain. VLM (Vision-Language Model) that can process images, screenshots, and video frames. Runs natively on Apple Silicon via MLX Metal.
## Architecture
- **Base Model:** Qwen3.5-9B VLM (9B params, vision + language)
- **Architecture:** `Qwen3_5ForConditionalGeneration` (multimodal)
- **Format:** MLX mxfp4 quantized (Apple Silicon native)
- **Size:** ~5.3 GB (includes vision encoder)
- **Vision:** Full image understanding, OCR, screenshot analysis, video frames
- **Note:** This is the censored (base) version. For uncensored, see OsirisCortex-v7-MLX.
## Usage
```python
from mlx_vlm import load, generate
model, processor = load("osirisbrain/OsirisCortex-v7-Censo-MLX")
output = generate(model, processor, "Describe this image", ["path/to/image.jpg"])
```
## Credits
Converted by [RepublicOfKorokke](https://huggingface.co/RepublicOfKorokke/Qwen3.5-9B-mlx-vlm-mxfp4).
Original model: [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) by Alibaba.
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