Document Question Answering
Transformers
PyTorch
English
document-processing
ocr
ner
text-classification
information-extraction
invoice
receipt
form
Instructions to use mrrobot2610/IDP-Machine-learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrrobot2610/IDP-Machine-learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="mrrobot2610/IDP-Machine-learning")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrrobot2610/IDP-Machine-learning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Initial commit: IDP (Intelligent Document Processing) System
- FastAPI backend with document processing pipeline - Next.js frontend for document upload and results display - Trained classifier model (MiniLM-L6) for document classification - Trained NER model (DistilBERT) for field extraction - OCR engine using EasyOCR - Pre/post-processing utilities - Demo mode for quick testing without GPU - Complete documentation and deployment guides1a7ee60