Here are a collection of a few resources you can use to help fine-tune your LLMs! 🪡 Fine-tuning Approaches: Fine-tuning gpt-3.5-turbo Notebook Purpose Link Structured Output Fine-tuning for GPT-3.5-turbo Simple fine-tuning example using the OpenAI fine-tuning endpoint Here Instruct-tuning LLaMA 2: Notebook Purpose Link Instruct-tuning with Flash Attention and QLoRA Supervised fine-tuning! Here Instruct-tuning OpenLM's OpenLLaMA on the Dolly-15k Dataset Notebooks: Notebook Purpose Link Instruct-tuning Leveraging QLoRA Supervised fine-tuning! Here Instruct-tuning Leveraging Lit-LLaMA Using Lightning-AI's Lit-LLaMA framework for Supervised fine-tuning Here Natural Language to SQL fine-tuning using Lit-LLaMA Using Lightning-AI's Lit-LLaMA framework for Supervised fine-tuning on the Natural Language to SQL task Here
