VARCO-VISION-14B-HF
| Property | Value |
|---|---|
| Parameter Count | 15.2B |
| Base Model | Qwen2.5-14B-Instruct |
| License | CC BY-NC 4.0 |
| Architecture | LLaVA-OneVision |
| Languages | English, Korean |
| Research Paper | LLaVA-OneVision Paper |
What is VARCO-VISION-14B-HF?
VARCO-VISION-14B-HF is a cutting-edge Vision-Language Model developed by NC Research's Multimodal Generation Team. This model represents a significant advancement in multimodal AI, capable of processing both images and text while supporting both English and Korean languages. Built upon the Qwen2.5-14B-Instruct foundation and utilizing the google/siglip-so400m-patch14-384 vision encoder, it excels in both multimodal and text-only tasks.
Implementation Details
The model implements the LLaVA-OneVision architecture and features sophisticated capabilities for processing visual and textual information. It requires transformers >= 4.45.0 and can be deployed with flash attention 2 for optimal performance.
- Supports single image and text input combinations
- Implements advanced grounding capabilities for object location identification
- Features built-in OCR functionality for text recognition in images
- Uses specialized tokens for various tasks (e.g., <gro>, <ocr>, <bbox>)
Core Capabilities
- Visual-textual understanding and generation
- Object grounding with bounding box coordinates
- OCR functionality for text extraction from images
- Bilingual support (English and Korean)
- Conversational abilities with structured chat templates
Frequently Asked Questions
Q: What makes this model unique?
VARCO-VISION-14B-HF stands out for its comprehensive multimodal capabilities, particularly its ability to handle both English and Korean, along with advanced features like object grounding and OCR. Its architecture and training approach allow it to achieve performance levels comparable to proprietary models.
Q: What are the recommended use cases?
The model is ideal for applications requiring visual-textual understanding, such as image description, object identification, text extraction from images, and bilingual conversational AI systems. It's particularly useful for applications needing precise object localization or text recognition within images.
