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Gemma 3 12b It Qat

Developed by unsloth
Gemma 3 is a lightweight, state-of-the-art multimodal open-source model launched by Google. It can process text and image inputs and generate text outputs, suitable for various text generation and image understanding tasks.
Downloads 952
Release Time : 4/21/2025

Model Overview

Gemma 3 is a multimodal model built on the same research and technology as the Gemini model. It supports text and image inputs and generates text outputs. It has a large 128K context window and supports over 140 languages, suitable for tasks such as question answering, summarization, and reasoning.

Model Features

Multimodal processing
Can process text and image inputs simultaneously and generate text outputs
Large context window
Has a large 128K context window, suitable for processing long texts and complex tasks
Multilingual support
Supports over 140 languages, with extensive language coverage
Lightweight design
Relatively small model size, suitable for deployment in resource-constrained environments
Quantization-aware training
Adopts QAT technology to maintain quality similar to bfloat16 while reducing memory requirements

Model Capabilities

Text generation
Image analysis
Multilingual processing
Code generation
Mathematical reasoning
Document summarization
Question answering system
Visual question answering

Use Cases

Content creation and communication
Text generation
Generate creative text formats such as poems, scripts, code, marketing copy, and email drafts
Chatbots and conversational AI
Provide a conversational interface for customer service, virtual assistants, or interactive applications
Image data extraction
Extract, interpret, and summarize visual data for text communication
Research and education
Natural language processing research
Serve as a basis for researchers to experiment with VLM and NLP technologies
Language learning tools
Support interactive language learning experiences, help with grammar correction or provide writing exercises
Knowledge exploration
Help researchers explore large amounts of text by generating summaries or answering questions on specific topics
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