Local LLM Fine-tuning on Mac (M1 16GB)

🤝 Your engineers use Claude but sales, ops and finance don't? I fix that for 50 to 200-person software companies: https://aibuilder.academy/yt/3PIqhdRzhxE Here, I show how to fine-tune an LLM locally using an M-series Mac. The example adapts Mistral 7b to respond to YT comments in my likeness. 📰 Blog: https://medium.com/towards-data-scien... 💻 GitHub Repo: https://github.com/ShawhinT/YouTube-B... 🎥 QLoRA:    • 3 Ways to Make a Custom AI Assistant | RAG...   🎥 Fine-tuning with OpenAI:    • 3 Ways to Make a Custom AI Assistant | RAG...   ▶️ Series Playlist:    • Large Language Models (LLMs)   More Resources: [1] MLX: https://ml-explore.github.io/mlx/buil... [2] Original code: https://github.com/ml-explore/mlx-exa... [3] MLX community: https://huggingface.co/mlx-community [4] Model: https://huggingface.co/mlx-community/... [5] LoRA paper: https://arxiv.org/abs/2106.09685 Intro - 0:00 Motivation - 0:56 MLX - 1:57 GitHub Repo - 3:30 Setting up environment - 4:09 Example Code - 6:23 Inference with un-finetuned model - 8:57 Fine-tuning with QLoRA - 11:22 Aside: dataset formatting - 13:54 Running local training - 16:07 Inference with finetuned model - 18:20 Note on LoRA rank - 22:03