README.md

metadata

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

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.