prithivMLmods/QvQ-KiE

QvQ KiE [Key Information Extractor] Adapter for Qwen2-VL-OCR-2B-Instruct

The QvQ KiE adapter is a fine-tuned version of the Qwen/Qwen2-VL-2B-Instruct model, specifically tailored for tasks involving Optical Character Recognition (OCR), image-to-text conversion, and math problem-solving with LaTeX formatting. This adapter enhances the model’s performance for multi-modal tasks by integrating vision and language capabilities in a conversational framework.

Key Features

1. Vision-Language Integration

• Seamlessly combines image understanding with natural language processing, enabling accurate image-to-text conversion.

2. Optical Character Recognition (OCR)

• Extracts and processes textual content from images with high precision, making it ideal for document analysis and information extraction.

3. Math and LaTeX Support

• Efficiently handles complex math problem-solving, outputting results in LaTeX format for easy integration into scientific and academic workflows.

4. Conversational Capabilities

• Equipped with multi-turn conversational capabilities, providing context-aware responses during interactions. This makes it suitable for tasks requiring ongoing dialogue and clarification.

5. Image-Text-to-Text Generation

• Supports input in various forms:
  • Images
  • Text
  • Image + Text (multi-modal)
• Outputs include descriptive or problem-solving text, depending on the input type.

6. Secure Weight Format

• Utilizes Safetensors for fast and secure model weight loading, ensuring both performance and safety during deployment.

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