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README.md
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---
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pipeline_tag: text-generation
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tags:
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- cortexp.cpp
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- featured
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---
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## Overview
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**Google** developed and released the **Gemma 3** series, featuring multiple model sizes with both pre-trained and instruction-tuned variants. These multimodal models handle both text and image inputs while generating text outputs, making them versatile for various applications. Gemma 3 models are built from the same research and technology used to create the Gemini models, offering state-of-the-art capabilities in a lightweight and accessible format.
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The Gemma 3 models include four different sizes with open weights, providing excellent performance across tasks like question answering, summarization, and reasoning while maintaining efficiency for deployment in resource-constrained environments such as laptops, desktops, or custom cloud infrastructure.
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## Variants
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### Gemma 3
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| No | Variant | Branch | Cortex CLI command |
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| -- | ------------------------------------------------------ | ------ | ----------------------------- |
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| 1 | [Gemma-3-1B](https://huggingface.co/cortexso/gemma3/tree/1b) | 1b | `cortex run gemma3:1b` |
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| 2 | [Gemma-3-4B](https://huggingface.co/cortexso/gemma3/tree/4b) | 4b | `cortex run gemma3:4b` |
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| 3 | [Gemma-3-12B](https://huggingface.co/cortexso/gemma3/tree/12b) | 12b | `cortex run gemma3:12b` |
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| 4 | [Gemma-3-27B](https://huggingface.co/cortexso/gemma3/tree/27b) | 27b | `cortex run gemma3:27b` |
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Each branch contains a default quantized version.
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## Key Features
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- **Multimodal capabilities**: Handles both text and image inputs
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- **Large context window**: 128K tokens
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- **Multilingual support**: Over 140 languages
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- **Available in multiple sizes**: From 1B to 27B parameters
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- **Open weights**: For both pre-trained and instruction-tuned variants
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## Use it with Jan (UI)
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1. Install **Jan** using [Quickstart](https://jan.ai/docs/quickstart)
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2. Use in Jan model Hub:
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```bash
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cortexso/gemma3
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```
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## Use it with Cortex (CLI)
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1. Install **Cortex** using [Quickstart](https://cortex.jan.ai/docs/quickstart)
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2. Run the model with command:
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```bash
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cortex run gemma3
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```
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## Credits
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- **Author:** Google
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- **Original License:** [Gemma License](https://ai.google.dev/gemma/terms)
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- **Papers:** [Gemma 3 Technical Report](https://storage.googleapis.com/deepmind-media/gemma/Gemma3Report.pdf)
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