Skip to content

Latest commit

 

History

History
32 lines (17 loc) · 3.16 KB

README.md

File metadata and controls

32 lines (17 loc) · 3.16 KB
Raw

Masa Datasets Collection

This repository is a curated collection of datasets scraped using the Masa protocol, focusing on a variety of data sources. Our datasets are meticulously organized, structured, and/or diarized to provide valuable data for AI developers and researchers for use in AI applications.

Contents

  • Podcast Data: A comprehensive dataset of diarized podcast episodes, including speaker identification and timestamps. Ideal for training AI in speech recognition, content analysis, and understanding speaker dynamics. Useful in RAG (Retrieval-Augmented Generation) for enhancing conversational AI, fine-tuning Large Language Models (LLMs) for podcast summarization, and pre-training AI agents to recognize different speakers.

  • YouTube Data: An extensive collection of YouTube video transcripts, diarized with speaker labels and timestamps. Supports AI research in video content analysis, automatic subtitle generation, and multimedia data integration. Essential for fine-tuning LLMs to generate accurate subtitles, pre-training models on diverse multimedia content, and integrating video data into RAG systems for enriched context understanding.

  • Tweet Data on Memcoins: A dataset containing tweets related to memcoins, capturing the dynamic and often volatile discussions surrounding cryptocurrency trends and meme-driven markets. Perfect for sentiment analysis AI models, predicting market trends using LLMs, and pre-training agents to understand social media discourse. Enhances RAG systems by providing real-time examples of market discussions for more accurate retrieval and generation tasks.

  • Elon Musk's Tweet Feed: A dataset of tweets from Elon Musk's feed, offering insights into the impact of influential figures on social media discourse and market movements. Invaluable for training AI in influence analysis, market reaction prediction, and communication pattern recognition. Useful for fine-tuning LLMs to understand the impact of public figures on social media, pre-training models on influential communication, and enhancing RAG systems with examples of impactful tweets.

Using the Masa Protocol

The Masa protocol is a decentralized data scraping and data pre-processing framework for AI developers, designed to scrape web data and pre-process it as structured data; diarized, vectorized, and annotated. The Masa protocolensures high-quality, structured datasets are available for use in AI applications.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contribution

We welcome contributions to our dataset collection! If you have a dataset that you believe would fit well in our collection, or if you have suggestions for improving our existing datasets, please feel free to submit a pull request or open an issue.

Acknowledgments

  • Special thanks to all worker nodes on the Masa Protocol who have made this project possible.
  • Our gratitude to the podcasters, YouTubers, and tweeters whose content has been included in this collection for research and educational purposes.

For more information on how to use these datasets or to contribute, please refer to the documentation or contact us directly.