NuExtract-2-2B
| Property | Value |
|---|---|
| Model Size | 2B parameters |
| Base Architecture | InternVL2.5 |
| Author | NuMind |
| Model URL | https://huggingface.co/numind/NuExtract-2-2B |
What is NuExtract-2-2B?
NuExtract-2-2B is a specialized AI model designed for structured information extraction tasks. It's part of the NuExtract 2.0 family, built on the InternVL2.5 architecture, offering powerful capabilities for both text and image processing. The model excels at extracting structured data according to predefined templates, making it particularly valuable for automated data extraction scenarios.
Implementation Details
The model implements a sophisticated template-based extraction system that supports various data types including verbatim strings, integers, dates, enums, and multi-label classifications. It's optimized for inference with flash attention and supports bfloat16 precision for efficient processing.
- Multimodal support for both text and image inputs
- Template-driven extraction with JSON-based schema definition
- Dynamic preprocessing for varying image sizes and aspect ratios
- Batched inference support for multiple inputs
Core Capabilities
- Structured data extraction from text and images
- Support for multiple data types including strings, numbers, dates, and enums
- Template generation from various formats (XML, YAML)
- Zero-shot and few-shot learning support
- Multilingual processing capabilities
Frequently Asked Questions
Q: What makes this model unique?
NuExtract-2-2B stands out for its specialized focus on structured information extraction and its ability to handle both text and images while following precise templates. The model can automatically generate extraction templates and supports multiple input formats, making it highly versatile for various extraction tasks.
Q: What are the recommended use cases?
The model is ideal for automated data extraction from documents and images, form processing, structured information parsing, and converting unstructured data into structured formats. It's particularly useful for businesses needing to process large volumes of documents or images with consistent data extraction requirements.
