Donut Base Finetuned Cord V2

What is Donut Base Finetuned Cord V2 ?

Donut Base Finetuned Cord V2 is a specialized AI model designed for document analysis, particularly focused on extracting information from Indonesian receipts. It is optimized to accurately identify and retrieve key details such as dates, amounts, items, and other relevant data from receipt documents. This model is a fine-tuned version of the Donut Base model, tailored for specific use cases in Indonesian languages and contexts.

Features

• High Accuracy for Indonesian Receipts: Specifically trained to handle receipts in Indonesian language and format. • Comprehensive Data Extraction: Capable of identifying and extracting dates, totals, items, and other relevant fields from receipts. • Efficient Processing: Optimized for quick and accurate document analysis. • General Document Understanding: While specialized for receipts, it can handle other document types to some extent. • Integration-Friendly: Designed to be easily integrated into workflows or applications requiring receipt data extraction.

How to use Donut Base Finetuned Cord V2 ?

1. Install the Model: Use the appropriate library or framework to load the Donut Base Finetuned Cord V2 model. This typically involves using the CORD library or similar tools.
2. Prepare the Document: Input an Indonesian receipt document, either as an image or text. Ensure the document is clear and legible for optimal results.
3. Process the Document: Run the document through the model to analyze and extract relevant information.
4. Extract Data: Retrieve the extracted fields (e.g., date, total amount, items) for further use in your application or workflow.

Example code snippet (pseudo-code):

from cord import DonutBaseFinetunedCordV2

model = DonutBaseFinetunedCordV2()
receipt_image = "path/to/indonesian_receipt.jpg"
result = model.process(receipt_image)
extracted_data = result.extract()

Frequently Asked Questions

1. What types of receipts does Donut Base Finetuned Cord V2 support?
Donut Base Finetuned Cord V2 is primarily designed for Indonesian receipts, including retail, food, and service receipts. It may work with other types of receipts to some extent, but accuracy is highest with Indonesian formats.

2. Can Donut Base Finetuned Cord V2 handle non-Indonesian receipts?
While the model is optimized for Indonesian receipts, it may still process receipts in other languages or formats, but accuracy will vary. For non-Indonesian receipts, consider using a more general-purpose document analysis model.

3. What formats does Donut Base Finetuned Cord V2 support?
The model supports images of receipts (e.g., PNG, JPG) and potentially PDF formats. Text-based input may also be supported, depending on the implementation.

4. Is Donut Base Finetuned Cord V2 useful for documents other than receipts?
While primarily designed for receipts, the model can be applied to other structured documents with similar layouts. However, its performance may not be as robust as models specifically trained for those documents.