byt5 base dutch ocr correction

Introduction

The BYT5 Dutch OCR Correction model is a finetuned byT5 model designed to correct Optical Character Recognition (OCR) mistakes in Dutch text. The model is based on the google/byt5-base architecture and is finetuned using the Dutch section of the OSCAR dataset.

Architecture

The model utilizes the byT5 architecture, which is a variant of the T5 (Text-to-Text Transfer Transformer) model. It is trained to handle text-to-text tasks, making it suitable for correcting text errors generated by OCR systems.

Training

The base model, google/byt5-base, was finetuned on the Dutch section of the OSCAR dataset to specialize in correcting OCR errors in Dutch sentences. This training process involved adjusting the model's parameters to improve performance on this specific task.

Guide: Running Locally

To use the BYT5 Dutch OCR Correction model locally, follow these steps:

1. Install the Transformers Library: Ensure you have the transformers library installed. You can do this using pip:

   pip install transformers
   

2. Load the Model and Tokenizer:

   from transformers import AutoTokenizer, T5ForConditionalGeneration
   
   tokenizer = AutoTokenizer.from_pretrained('ml6team/byt5-base-dutch-ocr-correction')
   model = T5ForConditionalGeneration.from_pretrained('ml6team/byt5-base-dutch-ocr-correction')
   

3. Prepare Input Text:

   example_sentence = "Ben algoritme dat op ba8i8 van kunstmatige inte11i9entie vkijwel geautomatiseerd een tekst herstelt met OCR fuuten."
   model_inputs = tokenizer(example_sentence, max_length=128, truncation=True, return_tensors="pt")
   

4. Generate Corrected Text:

   outputs = model.generate(**model_inputs, max_length=128)
   corrected_text = tokenizer.decode(outputs[0])
   print(corrected_text)
   

For efficient performance, especially on large datasets or for faster processing, consider using cloud GPUs from platforms like AWS, Google Cloud, or Azure.

License

The model and its components are provided under the terms and conditions specified by Hugging Face and the original creators. Ensure to review and comply with these when using or modifying the model.