colab-data-engineering

What problem does it solve?

This Skill addresses the challenges of data engineering for machine learning on Google Colab, providing tools for dataset preparation, augmentation, and versioning.

Core Features & Use Cases

• Dataset Preparation: Offers methods for loading and preparing datasets from various sources, including HuggingFace, web scraping, and local files.
• Data Augmentation: Provides techniques for text augmentation, including back-translation and synonym replacement.
• Synthetic Data Generation: Generates synthetic data for fine-tuning models, using LLMs and JSON-based instructions.
• Data Versioning: Enables pushing datasets to HuggingFace Hub, saving locally, and tracking with DVC.
• Use Case: Ideal for data scientists and ML engineers working on Colab who need to efficiently prepare and manage datasets for training and fine-tuning models.

Quick Start

Use the colab-data-engineering skill to load a dataset from HuggingFace and prepare it for training.