{"data":{"slug":"arahim3-mlx-tune","name":"mlx-tune","tagline":"Fine-tune LLMs on your Mac with Apple Silicon for various tasks including SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR.","github_url":"https://github.com/ARahim3/mlx-tune","owner":"ARahim3","repo":"mlx-tune","owner_avatar_url":"https://avatars.githubusercontent.com/u/41390319?v=4","primary_language":"Python","stars":1372,"forks":88,"topics":["apple-silicon","deep-learning","huggingface","large-language-models","llm","llm-finetuning","local-llm","lora","machine-learning","macos","mlx","on-device-ai","peft","speech-recognition","speech-to-text","text-to-speech","transformers","unsloth","vision-language-model","whisper"],"archived":false,"github_pushed_at":"2026-06-23T12:24:30+00:00","maintenance_label":"Steady","url":"https://www.graphcanon.com/tools/arahim3-mlx-tune","markdown_url":"https://www.graphcanon.com/tools/arahim3-mlx-tune.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/arahim3-mlx-tune","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=arahim3-mlx-tune","description":"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.","homepage_url":"https://arahim3.github.io/mlx-tune/","license":"Apache-2.0","open_issues":11,"watchers":11,"ai_summary":"mlx-tune offers tools to fine-tune large language models using Apple Silicon. Supports a wide range of tasks such as supervised fine-tuning (SFT), reinforcement learning from human preferences (RLHP), generative pre-trained transformer (GPT) retraining on prompt optimization (GRPO), vision, text-to-speech (TTS), speech-to-text (STT), embeddings generation, and optical character recognition (OCR). Framework is compatible with the UnSloth API.","readme_excerpt":"## Quick Start\n\n```python\nfrom mlx_tune import FastLanguageModel, SFTTrainer, SFTConfig\nfrom datasets import load_dataset\n\n---\n\n# Load any HuggingFace model (1B model for quick start)\nmodel, tokenizer = FastLanguageModel.from_pretrained(\n    model_name=\"mlx-community/Llama-3.2-1B-Instruct-4bit\",\n    max_seq_length=2048,\n    load_in_4bit=True,\n)\n\n---\n\n## Requirements\n\n- **Hardware**: Apple Silicon Mac (M1/M2/M3/M4/M5)\n- **OS**: macOS 13.0+\n- **Memory**: 8GB+ unified RAM (16GB+ recommended)\n- **Python**: 3.9+\n\n---\n\n## License\n\nApache 2.0 - See [LICENSE](LICENSE) file.","github_created_at":"2026-01-03T17:48:38+00:00","created_at":"2026-07-11T12:11:57.30551+00:00","updated_at":"2026-07-30T00:00:45.291818+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"},{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"}],"tags":[{"slug":"apple-silicon","name":"apple-silicon"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"huggingface","name":"huggingface"},{"slug":"large-language-models","name":"large language models"},{"slug":"llm","name":"llm"},{"slug":"llm-finetuning","name":"llm-finetuning"},{"slug":"local-llm","name":"local-llm"},{"slug":"lora","name":"lora"}],"trust":{"provenance":{"is_fork":false,"github_id":1127351142,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-30T00:00:44.352Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":3,"days_since_push":36,"last_release_at":"2026-06-23T12:24:30Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":46,"high_count":0,"last_scan_at":"2026-07-11T12:12:00.779Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-30T00:00:44.979Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-30T00:00:44.979Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-30T00:00:44.979Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["You need to fine-tune large language models on a Mac with Apple Silicon hardware","You aim to work specifically with tasks like SFT, RLHP, GRPO, vision-based, TTS, STT, embeddings generation, or OCR"],"when_not_to_use":["Your development environment is not based on macOS running on Apple Silicon","The specific tasks you are targeting do not align with the capabilities of mlx-tune such as those exclusive to alternative platforms or tools"],"source":"enrich:decision_facts","observed_at":"2026-07-14T17:59:22.772Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"mlx-tune targets Mac users with Apple Silicon for fine-tuning LLMs across SFT, RLHP, GRPO, vision, TTS, STT, embeddings, and OCR using tools compatible with the UnSloth API."}]}}