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Google Gemma 3 1b It Qat GGUF

Developed by bartowski
Multiple quantized versions based on Google Gemma 3B QAT weights, suitable for local inference deployment
Downloads 1,437
Release Time : 4/19/2025

Model Overview

This model is a collection of quantized versions of the Google Gemma-3-1B instruction-tuned model, optimized using llama.cpp's imatrix method for quantization, supporting multiple precision levels to adapt to different hardware environments

Model Features

Quantization-Aware Training Optimization
Based on Google's official QAT weights, offering better precision retention compared to traditional quantization methods
Multi-precision Options
Provides 20 quantization options from BF16 to 2bit to meet different hardware requirements
ARM Compatibility
Specific quantized versions (e.g., Q4_0) support online repacking inference on ARM CPUs
imatrix Optimization
Uses llama.cpp's imatrix feature for data-aware quantization, improving low-bit quantization quality

Model Capabilities

Instruction Following
Multi-turn Dialogue
Text Completion
Knowledge Q&A

Use Cases

Local Deployment Applications
Personal Assistant
Run a personalized AI assistant on local devices
Low-latency responses with privacy protection
Educational Tool
Offline learning tutoring and Q&A system
Edge Computing
Mobile Inference
Run AI features on mobile devices like smartphones
Optimized quantized models reduce hardware requirements
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