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---
language:
- en
tags:
- vision-language
- vqa
- text-to-image-evaluation
license: mit
---
# Tiny Random VQAScore Model
This is a tiny random version of the VQAScore architecture for educational and testing purposes.
## Model Architecture
- **Vision Encoder**: Tiny CNN + Transformer (64 hidden size)
- **Language Model**: Tiny Transformer (256 hidden size)
- **Multimodal Projector**: MLP with 256 → 128 → 64 → 1
## Usage
```python
from create_tiny_vqa_model import TinyVQAScore
# Load the model
model = TinyVQAScore(device="cpu")
# Score an image
from PIL import Image
image = Image.open("your_image.jpg")
score = model.score(image, "What is shown in this image?")
print(f"VQA Score: {score}")
```
## Model Size
- **Parameters**: ~50K (vs ~11B for the original XXL model)
- **Memory**: ~200KB (vs ~22GB for the original XXL model)
## Disclaimer
This is a randomly initialized model for testing and educational purposes. It is not trained and will not produce meaningful VQA results.
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