ARO Teacher (30B)
The full 30B MoE teacher model, fine-tuned on ARO training data. This model is used for:
- Distillation — generating high-quality training data for the smaller student model
- Iterative retraining — serving as the starting point for the next training cycle
- High-quality inference — when maximum accuracy is needed (at the cost of speed/memory)
For deployment and everyday use, prefer the distilled 8B student model: ARO-Lang/aro-coder-4bit
| Architecture | Qwen3 30B MoE (3.3B active parameters) |
| Base model | mlx-community/Qwen3-Coder-30B-A3B-Instruct-4bit |
| Quantization | 4-bit (MLX) |
| Size | ~16 GB |
| Training source | dpo |
Usage
from mlx_lm import load, generate
model, tokenizer = load("ARO-Lang/aro-teacher-30b-4bit")
Or as a base for continued fine-tuning:
python -m mlx_lm lora --model ARO-Lang/aro-teacher-30b-4bit --data ./train_data --train
Links
- Distilled student: ARO-Lang/aro-coder-4bit
- Website: arolang.github.io/aro
- GitHub: github.com/arolang/aro
- Language Guide: Wiki
License
MIT License
- Downloads last month
- 68
Model size
31B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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4-bit
Model tree for ARO-Lang/aro-teacher-30b-4bit
Base model
Qwen/Qwen3-Coder-30B-A3B-Instruct