OsirisHippocampus-Vision-v7-MLX
The Hippocampus — Osiris's visual cortex. A lightweight 3B VLM that processes screenshots, images, and visual input. Runs natively on Apple Silicon via MLX Metal.
Architecture
- Base Model: Qwen2.5-VL-3B-Instruct (3B parameters, vision-language)
- Format: MLX 4-bit quantized (Apple Silicon native)
- Size: ~2.9 GB
- Speed: ~150+ tokens/sec on M2 Pro
- Capabilities: OCR, screenshot analysis, image understanding, visual QA
Usage
from mlx_vlm import load, generate
model, processor = load("osirisbrain/OsirisHippocampus-Vision-v7-MLX")
output = generate(model, processor, "What do you see in this image?", ["screenshot.png"])
Credits
MLX conversion by mlx-community. Original model: Qwen/Qwen2.5-VL-3B-Instruct by Alibaba.
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Model size
1B params
Tensor type
F16
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U32 ·
Hardware compatibility
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Quantized
Model tree for osirisbrain/OsirisHippocampus-Vision-v7-MLX
Base model
Qwen/Qwen2.5-VL-3B-Instruct
# 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/OsirisHippocampus-Vision-v7-MLX") config = load_config("osirisbrain/OsirisHippocampus-Vision-v7-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)