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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

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A collection of fine-tuning notebooks!

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