Dataset

Overview

The Dataset page in LLM Labs collects all datasets available for automated evaluation or fine-tuning, providing a centralized location for managing your data.

Prerequisites

Dataset must be formatted as a CSV (Comma Separated Value) file with the following two columns:

  1. prompt: This column contains the input prompt that you will feed to your LLM.

  2. expected_completion: This column holds the desired or ideal output that your LLM should generate in response to the given prompt.

Create dataset

  1. Navigate to the Dataset menu on the left sidebar.

  2. Click the Create dataset button.

  3. Type the dataset name, and you will be redirected to the prompt pairs table.

  4. Click Upload dataset button and select a .csv containing 2 columns: prompts and expected completions.

  5. Once the file is uploaded, the dataset will automatically be added to the table.

Modify dataset item

Once a dataset is uploaded, you can add, edit, or delete dataset item.

Add more dataset items

  1. Click Add dataset button next to the Search field.

  2. Upload the .csv file.

  3. The additional datasets will be added to the table.

Edit dataset item

  1. Find the dataset item you want to edit using the search field.

  2. Right-click the dataset item, then click the Edit option.

  3. Modify the necessary details, then click Enter to apply the updates.

Delete dataset item

  1. Find the dataset item you want to edit using the Search field.

  2. Right-click the dataset item, then click the Delete option.

  3. The dataset item is deleted.

Please note that this action cannot be undone.

Delete dataset

  1. In the main Dataset page, find the dataset you want to delete using the Search field or filter options.

  2. Click on the triple-dot menu, then select Delete option. Confirm the deletion by clicking the Delete button.

To delete multiple datasets:

  1. Select the datasets and click Delete icon above the table.

  2. Confirm the deletion by clicking the Delete button.

Access via Automated evaluation

Once you've created the dataset, it will be available for use in the Automated evaluation projects. Learn more about Automated evaluation.

Access via Fine-tuning

Once you've created the dataset, it will be available for use for fine-tuningmodels. Learn more about Fine-tuning models.

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