| --- |
| library_name: transformers |
| language: en |
| license: mit |
| --- |
| |
| # BART-base-ocr |
| This model is released as part of the paper [Leveraging LLMs for Post-OCR Correction of Historical Newspapers](https://aclanthology.org/2024.lt4hala-1.14/) and designed to correct OCR text. [BART-base](https://huggingface.co/facebook/bart-base) is fine-tuned for post-OCR correction of historical English, using [BLN600](https://aclanthology.org/2024.lrec-main.219/), a parallel corpus of 19th century newspaper machine/human transcription. |
|
|
| ## Usage |
| ```python |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline |
| |
| model = AutoModelForSeq2SeqLM.from_pretrained('pykale/bart-base-ocr') |
| tokenizer = AutoTokenizer.from_pretrained('pykale/bart-base-ocr') |
| generator = pipeline('text2text-generation', model=model.to('cuda'), tokenizer=tokenizer, device='cuda', max_length=1024) |
| |
| ocr = "The defendant wits'fined �5 and costs." |
| pred = generator(ocr)[0]['generated_text'] |
| print(pred) |
| ``` |
|
|
| ## Citation |
| ``` |
| @inproceedings{thomas-etal-2024-leveraging, |
| title = "Leveraging {LLM}s for Post-{OCR} Correction of Historical Newspapers", |
| author = "Thomas, Alan and Gaizauskas, Robert and Lu, Haiping", |
| editor = "Sprugnoli, Rachele and Passarotti, Marco", |
| booktitle = "Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024", |
| month = "may", |
| year = "2024", |
| address = "Torino, Italia", |
| publisher = "ELRA and ICCL", |
| url = "https://aclanthology.org/2024.lt4hala-1.14", |
| pages = "116--121", |
| } |
| ``` |
