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Vilt Gqa Ft

Developed by phucd
A vision-language model based on ViLT architecture, fine-tuned specifically for GQA visual reasoning tasks
Text-to-Image
Transformers
#Visual Reasoning#Multimodal QA#Real-world Scene Understanding
Downloads 62
Release Time : 4/18/2025

Model Overview

This model is a vision-language model based on the ViLT (Vision-and-Language Transformer) architecture, fine-tuned on the GQA (real-world visual reasoning dataset), excelling at handling visual reasoning tasks.

Model Features

Joint Vision-Language Modeling
Adopts ViLT architecture to process both visual and linguistic inputs simultaneously, achieving cross-modal understanding
GQA Dataset Fine-tuning
Specifically optimized for the GQA visual reasoning dataset to enhance real-world scene reasoning capabilities
Efficient Training
Uses techniques like gradient accumulation to optimize training efficiency, achieving a batch size of 32

Model Capabilities

Visual Question Answering
Image Understanding
Cross-modal Reasoning
Scene Understanding

Use Cases

Smart Assistants
Image Content Q&A
Answer complex questions about image content
Capable of understanding image scenes and answering reasoning-based questions
Education
Visual Learning Aid
Assist students in understanding complex visual scenes
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