FiddleCube

What is FiddleCube?

FiddleCube is a specialized product for data science that quickly generates question and answer pairs from user data to help assess large language models (LLMs). It provides accurate gold datasets, supports multiple question types, and uses metrics to evaluate data accuracy. Additionally, it includes diagnostic tools to identify and improve underperforming queries.

Who Can Benefit?

Data scientists, machine learning engineers, and researchers evaluating language model performance can benefit from FiddleCube. It helps solve the challenge of creating high-quality datasets, improving model assessment efficiency and accuracy.

Example Usage:

Oren Dar from Intuit finds FiddleCube addresses core challenges in creating high-quality datasets. She-Lan from Interval Works discovered through Y Combinator that FiddleCube solves all problems and is excellent. Shiv from Athina.ai says FiddleCube makes quality evaluation datasets easily accessible where they were previously lacking.

Key Features:

Easily integrate with just two lines of code into existing projects.

Supports over eight question types ensuring comprehensive testing.

Accuracy scoring based on metrics to filter low-quality data.

Quickly generate high-quality datasets.

Run diagnostics with root cause analysis and improvement suggestions.

Support for custom integration and self-hosting to protect data privacy.

Getting Started:

1. Visit the FiddleCube website and sign up for an account.

2. Choose a suitable plan, such as free or enterprise options.

3. Integrate the provided code into your project.

4. Use FiddleCube to generate question and answer pairs and assess your dataset.

5. Utilize FiddleCube’s diagnostic tools to identify and improve performance issues.

6. Adjust question types and datasets based on feedback to enhance evaluation accuracy.