AIDir.app
  • Hot AI Tools
  • New AI Tools
  • AI Tools Category
AIDir.app
AIDir.app

Save this website for future use! Free to use, no login required.

About

  • Blog

© 2025 • AIDir.app All rights reserved.

  • Privacy Policy
  • Terms of Service
Home
Dataset Creation
Github To Huggingface Dataset Migration Tool

Github To Huggingface Dataset Migration Tool

Migrate datasets from GitHub to Hugging Face Hub

You May Also Like

View All
💻

Function Calling Datasets Explorer

Browse and view Hugging Face datasets from a collection

7
🏆

Submit

Generate a Parquet file for dataset validation

0
🐶

Convert to Safetensors

Convert a model to Safetensors and open a PR

0
⚗

Distilabel Synthetic Data Pipeline Finder

Find and view synthetic data pipelines on Hugging Face

12
🐨

Fast

Organize and process datasets efficiently

0
🚀

GPT-Fine-Tuning-Formatter

Validate JSONL format for fine-tuning

4
👁

Sarthaksavvy Flux Lora Train

Train a model using custom data

1
🏷

Argilla Space Template

Manage and annotate datasets

0
🦀

Upload To Hub

Upload files to a Hugging Face repository

0
✍

Math

Annotation Tool

0
🌐

🌐📄💾🏛️WebCopyData.Gov

Browse and search datasets

1
🚀

gradio_huggingfacehub_search V0.0.7

Search for Hugging Face Hub models

15

What is Github To Huggingface Dataset Migration Tool ?

The Github To Huggingface Dataset Migration Tool is a utility designed to simplify the process of migrating datasets from GitHub repositories to the Hugging Face Hub. It enables users to seamlessly transfer their dataset files, maintaining the integrity and structure of the data. This tool is particularly useful for researchers and data scientists who want to leverage Hugging Face's ecosystem for dataset sharing, versioning, and collaboration.

Features

• Support for GitHub Repositories: Migrate datasets stored in public or private GitHub repositories.
• Dataset Versioning: Preserve dataset versions during the migration process.
• Large Dataset Handling: Efficiently manage and transfer large-scale datasets.
• Data Format Compatibility: Supports various data formats commonly used in machine learning workflows.
• Integration with Hugging Face Libraries: Compatibility with Hugging Face's ecosystem, including datasets and transformers libraries.
• Repository Structure Mapping: Maintain the original folder and file structure of the dataset during migration.
• Commit History Preservation: Optionally retain commit history and metadata from GitHub.
• Validation and Verification: Ensure data integrity through pre- and post-migration checks.

How to use Github To Huggingface Dataset Migration Tool ?

  1. Install the Tool: Install the migration tool using pip or directly from the source code.
  2. Authenticate with Hugging Face: Configure your Hugging Face credentials to access the Hub.
  3. Clone GitHub Repository: Clone the GitHub repository containing the dataset to your local machine.
  4. Create a Dataset Configuration: Define a configuration file specifying the dataset metadata and requirements.
  5. Run the Migration Script: Execute the migration script, providing the path to the cloned repository and the configuration file.
  6. Review and Push: Review the migrated dataset and push it to the Hugging Face Hub.

Frequently Asked Questions

What types of GitHub repositories are supported?
The tool supports both public and private GitHub repositories. For private repositories, ensure you have the necessary authentication credentials.

Can I migrate datasets that are split across multiple repositories?
Yes, the tool allows you to specify multiple repositories or subdirectories within a repository to migrate as a single dataset.

How are dataset versions handled during migration?
The tool preserves the version history by creating separate versions on Hugging Face Hub. You can also choose to create a new version or overwrite an existing one.

Recommended Category

View All
🧹

Remove objects from a photo

↔️

Extend images automatically

🖼️

Image Captioning

⬆️

Image Upscaling

🖌️

Image Editing

🖼️

Image

📄

Extract text from scanned documents

⭐

Recommendation Systems

🎬

Video Generation

​🗣️

Speech Synthesis

✂️

Separate vocals from a music track

✨

Restore an old photo

🗒️

Automate meeting notes summaries

🤖

Create a customer service chatbot

🎵

Generate music