Source: deepreinforce-ai/Ornith-1.0-9B (license: mit)
Tool: mlx-vlm 0.6.3 — mlx_vlm.convert --hf-path deepreinforce-ai/Ornith-1.0-9B --mlx-path . -q --q-bits 4 --q-group-size 64
Effective: 5.059 bits/weight
Validation: reproduced geometrically exact CAD output in an agentic CAD+FEM pipeline (volumes match the reference mlx-community conversion).

Usage

python

from mlx_vlm import load, generate
model, processor = load("ToPo-ToPo/Ornith-1.0-9B-mlx-4bit")