Multimodal retrieval using llamaindex/vdr-2b-multi-v1
Next-generation reasoning model that runs locally in-browser
Analyze legal PDFs and answer questions
Search documents and retrieve relevant chunks
Extract text from document images
Find relevant text chunks from documents based on queries
Search documents using semantic queries
Extract text from multilingual invoices
Extract text from documents or images
Search for similar text in documents
Analyze documents to extract and structure text
Extract text from images using OCR
Find information using text queries
The Multimodal VDR Demo is a powerful tool designed for extracting text from scanned documents using advanced multimodal retrieval technology. It leverages the llamaindex/vdr-2b-multi-v1 model to enable search functionality across documents using both text and images. This innovative approach allows users to analyze and retrieve information from scanned documents with high accuracy.
• Multimodal Search: Combine text and image-based queries for robust document retrieval.
• Text Extraction: Accurately extract text from scanned documents with image content.
• Scanned Document Support: Works with scanned documents containing text and images.
• Large Language Model Integration: Utilizes the advanced capabilities of the llamaindex/vdr-2b-multi-v1 model.
• Zero-Shot Capability: No additional training required for new documents.
What formats does the Multimodal VDR Demo support?
The demo supports scanned documents in formats like PDF, PNG, and JPEG.
How does image quality affect text extraction?
Higher-quality images with clear text generally yield better extraction results.
What makes this different from traditional OCR tools?
The Multimodal VDR Demo combines text and image-based retrieval, offering more versatile search and extraction capabilities compared to traditional OCR tools.