ColVintern-1B-v1
| Property | Value |
|---|---|
| Parameter Count | 938M |
| Model Type | Visual Language Model |
| Languages | Vietnamese, English |
| Tensor Type | BF16 |
| Base Model | Vintern-1B-v2 |
What is ColVintern-1B-v1?
ColVintern-1B-v1 is a groundbreaking bilingual visual language model that implements the Colpali pipeline for Vietnamese and English document understanding. Built on Vintern-1B-v2, this model represents a significant advancement in efficient multimodal processing, achieving comparable results to larger 2B-3B parameter models while maintaining a compact 938M parameter size.
Implementation Details
The model leverages advanced RAG capabilities through embedding vector extraction for both questions and images. It was trained on the Colpali dataset and specialized Vietnamese image-based QA pairs, demonstrating impressive performance across various document understanding benchmarks.
- Achieves 78.8% average accuracy across diverse benchmarks
- Specialized in processing Vietnamese and English text
- Implements late interaction architecture for optimal performance
- Supports efficient document retrieval and question answering
Core Capabilities
- Bilingual document understanding and analysis
- Visual question answering for complex documents
- Embedding vector extraction for retrieval tasks
- High performance on specialized Vietnamese content
- Efficient processing with reduced parameter count
Frequently Asked Questions
Q: What makes this model unique?
ColVintern-1B-v1 stands out for its efficient architecture that achieves near-Colpali v1 performance with only 1B parameters, while adding robust Vietnamese language support. It's specifically optimized for document understanding and visual question answering tasks.
Q: What are the recommended use cases?
The model excels in document analysis, visual question answering, and information retrieval tasks, particularly for Vietnamese and English content. It's ideal for applications requiring document understanding, such as automated document processing, content analysis, and information extraction systems.
