What is the difference between pre-training, fine-tuning, and instruct-tuning exactly?

I am very new to the LLM field. I have two questions:


1. What is the difference between pre-training, fine-tuning, and instruct-tuning? I am not asking for exact definitions. I understand pre-training means training from scratch, but I am confused about fine-tuning and instruct tuning.
2. If I have my own dataset and want to add new knowledge to an existing model (Mixtral, etc.), should I go with pre-training, instruct tuning, or fine-tuning? The confusion comes because instruct tuning means …

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