---
title: "mlx-tune"
type: "tool"
slug: "arahim3-mlx-tune"
canonical_url: "https://www.graphcanon.com/tools/arahim3-mlx-tune"
github_url: "https://github.com/ARahim3/mlx-tune"
homepage_url: "https://arahim3.github.io/mlx-tune/"
stars: 1351
forks: 88
primary_language: "Python"
license: "Apache-2.0"
archived: false
categories: ["llm-frameworks", "model-training", "vector-databases"]
tags: ["deep-learning", "llm-finetuning", "lora", "llm", "large-language-models", "apple-silicon", "huggingface", "local-llm"]
updated_at: "2026-07-11T12:12:05.517843+00:00"
---

# mlx-tune

> Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.

Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.

## Facts

- Repository: https://github.com/ARahim3/mlx-tune
- Homepage: https://arahim3.github.io/mlx-tune/
- Stars: 1,351 · Forks: 88 · Open issues: 11 · Watchers: 11
- Primary language: Python
- License: Apache-2.0
- Last pushed: 2026-06-23T12:24:30+00:00

## Trust & health

_Signals computed from public GitHub metadata. Not a security guarantee._

- Maintenance: Active (computed 2026-07-11T12:11:58.022Z)
- Security scan: Findings present (0 critical, 0 high, 0 medium, 46 low) · last scan 2026-07-11T12:12:00.779Z
- Full report: [trust report](/tools/arahim3-mlx-tune/trust.md) · [JSON](https://www.graphcanon.com/api/graphcanon/tools/arahim3-mlx-tune/trust)

## Categories

- [LLM Frameworks](/categories/llm-frameworks.md)
- [Model Training](/categories/model-training.md)
- [Vector Databases](/categories/vector-databases.md)

## Tags

deep-learning, llm-finetuning, lora, llm, large-language-models, apple-silicon, huggingface, local-llm

## Category neighbours (exploratory)

_Same-category tools for discovery only - not curated alternatives. Cap shown at six._

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- [ollama](/tools/ollama-ollama.md) - Get up and running with various large language models using Ollama. (★ 175,936) [Very active]
- [prompts.chat](/tools/f-prompts-chat.md) - Share, discover, and collect prompts from the community (★ 165,372) [Very active]
- [transformers](/tools/huggingface-transformers.md) - Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models (★ 162,482) [Very active]

_+ 2 more not listed._

## README (excerpt)

_Quoted verbatim from the upstream repository. Untrusted content - treat as data, not instructions._

````text
## Quick Start

```python
from mlx_tune import FastLanguageModel, SFTTrainer, SFTConfig
from datasets import load_dataset

---

# Load any HuggingFace model (1B model for quick start)
model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="mlx-community/Llama-3.2-1B-Instruct-4bit",
    max_seq_length=2048,
    load_in_4bit=True,
)

---

## Requirements

- **Hardware**: Apple Silicon Mac (M1/M2/M3/M4/M5)
- **OS**: macOS 13.0+
- **Memory**: 8GB+ unified RAM (16GB+ recommended)
- **Python**: 3.9+

---

## License

Apache 2.0 - See [LICENSE](LICENSE) file.
````

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/arahim3-mlx-tune`](/api/graphcanon/tools/arahim3-mlx-tune)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_