Create README.md

README.md

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+---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- en
+license:
+- unknown
+multilinguality:
+- monolingual
+pretty_name: Team-PIXEL/rendered-bookcorpus
+size_categories:
+- 1M<n<10M
+source_datasets:
+- rendered|BookCorpusOpen
+task_categories:
+- masked-auto-encoding
+- rendered-language-modelling
+task_ids:
+- masked-auto-encoding
+- rendered-language-modeling
+paperswithcode_id: bookcorpus
+---
+
+# Dataset Card for BookCorpusOpen
+
+## Dataset Description
+
+- **Homepage:** [https://github.com/xplip/pixel](https://github.com/xplip/pixel)
+- **Repository:** [https://github.com/xplip/pixel](https://github.com/xplip/pixel)
+- **Papers:** [Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books
+](https://arxiv.org/abs/1506.06724), [Language Modelling with Pixels](https://arxiv.org/abs/2207.06991)
+- **Point of Contact:** [Phillip Rust](mailto:[email protected])
+- **Size of downloaded dataset files:** 63.58 GB
+- **Size of the generated dataset:** 63.59 GB
+- **Total amount of disk used:** 127.17 GB
+
+### Dataset Summary
+
+This dataset is a version of the BookCorpus available at [https://huggingface.co/datasets/bookcorpusopen](https://huggingface.co/datasets/bookcorpusopen) with examples rendered as images with resolution 16x8464 pixels. 
+
+The original BookCorpus was introduced by Zhu et al. (2015) in [Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books](https://arxiv.org/abs/1506.06724) and contains 17868 books of various genres. The rendered BookCorpus was used to train the [PIXEL](https://huggingface.co/Team-PIXEL/pixel-base) model introduced in the paper [Language Modelling with Pixels](https://arxiv.org/abs/2207.06991) by Phillip Rust, Jonas F. Lotz, Emanuele Bugliarello, Elizabeth Salesky, Miryam de Lhoneux, and Desmond Elliott.
+
+The BookCorpusOpen dataset was rendered book-by-book into 5.4M examples containing approximately 1.1B words in total. The dataset is stored as a collection of 162 parquet files. It was rendered using the script openly available at [https://github.com/xplip/pixel/blob/main/scripts/data/prerendering/prerender_bookcorpus.py](https://github.com/xplip/pixel/blob/main/scripts/data/prerendering/prerender_bookcorpus.py). The text renderer uses a PyGame backend and a collection of merged Google Noto Sans fonts. The PyGame backend does not support complex text layouts (e.g. ligatures and right-to-left scripts) or emoji, so occurrences of such text in the BookCorpus have not been rendered accurately.
+Each example consists of a "pixel_values" field which stores a 16x8464 (height, width) grayscale image containing the rendered text, and an integer value "num_patches" which stores how many image patches (when splitting the image into 529 non-overlapping patches of resolution 16x16 pixels) in the associated images contain actual text, i.e. are neither blank (fully white) nor are the fully black end-of-sequence patch.
+
+## Dataset Structure
+
+### Data Instances
+
+- **Size of downloaded dataset files:** 63.58 GB
+- **Size of the generated dataset:** 63.59 GB
+- **Total amount of disk used:** 127.17 GB
+
+An example of 'train' looks as follows.
+```
+{
+    "pixel_values": <PIL.PngImagePlugin.PngImageFile image mode=L size=8464x16
+    "num_patches": "498"
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+- `pixel_values`: an `Image` feature.
+- `num_patches`: a `Value(dtype="int64")` feature.
+
+### Data Splits
+
+|train|
+|:----|
+|5400000|
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the source language producers?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the annotators?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Personal and Sensitive Information
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Discussion of Biases
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Other Known Limitations
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Licensing Information
+
+The books have been crawled from smashwords.com, see their [terms of service](https://www.smashwords.com/about/tos) for more information.
+
+A data sheet for this dataset has also been created and published in [Addressing "Documentation Debt" in Machine Learning Research: A Retrospective Datasheet for BookCorpus](https://arxiv.org/abs/2105.05241)
+
+### Citation Information
+
+```bibtex
+@InProceedings{Zhu_2015_ICCV,
+    title = {Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books},
+    author = {Zhu, Yukun and Kiros, Ryan and Zemel, Rich and Salakhutdinov, Ruslan and Urtasun, Raquel and Torralba, Antonio and Fidler, Sanja},
+    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
+    month = {December},
+    year = {2015}
+}
+```
+
+```bibtex
+@article{rust-etal-2022-pixel,
+  title={Language Modelling with Pixels},
+  author={Phillip Rust and Jonas F. Lotz and Emanuele Bugliarello and Elizabeth Salesky and Miryam de Lhoneux and Desmond Elliott},
+  journal={arXiv preprint},
+  year={2022},
+  url={https://arxiv.org/abs/2207.06991}
+}
+```
+
+
+### Contact Person
+
+This dataset was added by Phillip Rust.
+
+Github: [@xplip](https://github.com/xplip)
+
+Twitter: [@rust_phillip](https://twitter.com/rust_phillip)