| Sharing mlx-tune, a Python library for fine-tuning LLMs natively on Apple Silicon using Apple's MLX framework. It supports SFT, DPO, ORPO, GRPO, KTO, SimPO trainers with proper loss implementations, plus vision-language model fine-tuning (tested with Qwen3.5). The API mirrors Unsloth/TRL, so the same training script runs on Mac and CUDA — you only change the import line. Built on top of mlx-lm and mlx-vlm. LoRA/QLoRA, chat templates for 15 model families, GGUF export. Runs on 8GB+ unified RAM. Not a replacement for Unsloth on NVIDIA — this is for prototyping locally on Mac before scaling to cloud GPUs. [link] [comments] |
[P] mlx-tune – Fine-tune LLMs on Apple Silicon with MLX (SFT, DPO, GRPO, VLM)
Reddit r/MachineLearning / 3/17/2026
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Key Points
- mlx-tune is a Python library that enables fine-tuning LLMs natively on Apple Silicon using Apple's MLX framework.
- It supports SFT, DPO, ORPO, GRPO, KTO, SimPO trainers with proper loss implementations, plus vision-language model fine-tuning (tested with Qwen3.5); the API mirrors Unsloth/TRL so the same training script runs on Mac and CUDA by simply changing the import line.
- It runs on 8GB+ unified RAM and is built on mlx-lm and mlx-vlm, with LoRA/QLoRA, chat templates for 15 model families, and GGUF export.
- It is not a replacement for Unsloth on NVIDIA and is intended for local prototyping on Mac before scaling to cloud GPUs; GitHub: https://github.com/ARahim3/mlx-tune
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