A Step By Step Guide

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Crafting Your Own Dataset for Fine-Tuning Llama2

A Step-by-Step Guide

Part 2 by Sadat Shahriar

In this article, we will continue our journey of fine-tuning Llama2 for instruction following tasks. In the previous part, we discussed how to load a pre-trained Llama2 model and some of the important aspects of instruction following datasets. In this part, we will focus on creating your own custom dataset for fine-tuning Llama2.

To create your own dataset, you will need to follow a few steps:

1. Gather your data. This can be done by scraping the web, collecting data from a database, or creating your own data.
2. Format your data. The data should be in a format that Llama2 can understand. This means that the data should be in a JSON format.
3. Tokenize your data. This step breaks down the data into smaller units that Llama2 can understand.
4. Encode your data. This step converts the tokens into a numeric representation that Llama2 can understand.
5. Train your model. This step teaches Llama2 how to perform the task you are interested in.

Once you have completed these steps, you will have a custom dataset that you can use to fine-tune Llama2.

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