Datasets:
| language: | |
| - en | |
| license: cc0-1.0 | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: storytracer/LoC-PD-Books | |
| task_categories: | |
| - text-generation | |
| - feature-extraction | |
| dataset_info: | |
| - config_name: default | |
| features: | |
| - name: lccn | |
| dtype: string | |
| - name: title | |
| dtype: string | |
| - name: author | |
| dtype: string | |
| - name: year | |
| dtype: int64 | |
| - name: page_count | |
| dtype: int64 | |
| - name: filename | |
| dtype: string | |
| - name: text | |
| dtype: string | |
| - name: label | |
| dtype: string | |
| - name: score | |
| dtype: float64 | |
| splits: | |
| - name: train | |
| num_bytes: 2788098633.628336 | |
| num_examples: 8816 | |
| download_size: 1435586557 | |
| dataset_size: 2788098633.628336 | |
| - config_name: en-clean | |
| features: | |
| - name: lccn | |
| dtype: string | |
| - name: title | |
| dtype: string | |
| - name: author | |
| dtype: string | |
| - name: year | |
| dtype: int64 | |
| - name: page_count | |
| dtype: int64 | |
| - name: filename | |
| dtype: string | |
| - name: text | |
| dtype: string | |
| - name: score | |
| dtype: float64 | |
| splits: | |
| - name: train | |
| num_bytes: 1906155961.9587114 | |
| num_examples: 6399 | |
| download_size: 1055862380 | |
| dataset_size: 1906155961.9587114 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - config_name: en-clean | |
| data_files: | |
| - split: train | |
| path: en-clean/train-* | |
| tags: | |
| - books | |
| # LoC-PD-Books: preprocessed | |
| This is the `storytracer/LoC-PD-Books` dataset with the following preprocessing steps: | |
| - apply [clean-text](https://pypi.org/project/clean-text/) package keeping casing and newlines | |
| - drop OCR garbled text in first few lines of each example | |
| - fix (most) 'hard' newlines w/ regex similar to [gutenberg clean](https://huggingface.co/datasets/BEE-spoke-data/gutenberg-en-v1-clean) | |
| - 'grade' first 512 tokens of each book with [this quantized model](https://huggingface.co/pszemraj/gibberish_detector_onnx-quant-avx512_vnni); keep examples from labels `clean` (all) and `mild gibberish` w/ score 0.9 or higher | |
| --- | |