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Paligemma2 28b Mix 224

Developed by google
PaliGemma 2 is an upgraded vision-language model launched by Google, combining the capabilities of Gemma 2 and SigLIP vision models, supporting multilingual image-text interaction tasks.
Downloads 2,050
Release Time : 11/22/2024

Model Overview

A multimodal model built on Gemma 2 and SigLIP, excelling in vision-language tasks such as image caption generation, visual question answering, and object detection, offering two versions: mix (direct use) and pt (for fine-tuning).

Model Features

Unified Multi-task Framework
Supports 8 types of tasks including description generation, OCR, and Q&A through specific prompt templates without modifying the model architecture.
Open Component Integration
Combines the strengths of SigLIP vision model and Gemma 2 language model to achieve high-performance multimodal understanding.
Responsible Data Filtering
Training data undergoes multi-layered safety filtering for explicit content, toxic text, and personal information.

Model Capabilities

Short image caption generation
Detailed image caption generation
Multilingual optical character recognition
Visual question answering
Question generation
Object detection
Instance segmentation
Multilingual text generation

Use Cases

Content Understanding
Automatic Image Tagging
Generates high-quality descriptive text for images
Supports both short descriptions (similar to COCO) and long description modes.
Document Digitization
Extracts printed/handwritten text from images
Achieves multilingual text recognition via the 'ocr' instruction.
Intelligent Interaction
Visual Q&A System
Answers natural language questions about image content
Supports the 'answer {lang} {question}' instruction format.
Educational Assistant Tool
Automatically generates quiz questions based on image content
Uses the 'question {lang} {answer}' instruction to reverse-generate questions.
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