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Pile (The)
The Pile is a large-scale dataset of raw unprocessed text created by EleutherAI, which was designed to enable the training of large language models like GPT-J. The dataset is a collection of web pages, books, and scientific papers, totalling over 800GB of uncompressed text data.
The Pile is designed to be diverse and representative of the types of text that a language model like GPT-J might encounter in the real world. The dataset contains a wide range of topics, styles, and formats, and includes text in multiple languages. In addition, the Pile is designed to be constantly evolving, with new data added on an ongoing basis to reflect the changing nature of the web and the world at large.
By training on the Pile, GPT-J is able to learn from a vast and diverse corpus of text data, which enables it to generate high-quality and contextually appropriate text in a wide range of domains and applications.
Where can I download it?
Download keeps failing in the browser, is there another way to download?
Yes, I've used UGet download manager from https://ugetdm.com/
How do I use it?
To use the Pile for natural language processing tasks, such as language modelling or text classification, the raw text needs to be pre-processed and tokenized into a format that can be fed into a machine learning algorithm. This typically involves cleaning the text, removing unwanted characters or symbols, splitting the text into sentences or paragraphs, and then tokenizing each sentence or paragraph into a sequence of words or subword units.
Is there a pre-processed version I could download?
Hugging Face team has already pre-processed the Pile dataset and provided pre-processed versions of the data that are compatible with their Transformers library. These pre-processed versions include tokenized versions of the data, as well as additional metadata and annotations that can be used to train and evaluate language models or other natural language processing models.
Go to https://huggingface.co/datasets/the_pile/tree/main and download the_pile.py and run this to download all 800GB+ of it.