Gemma Model Plugin for DashAI

This plugin integrates Google's Gemma 3 language models into the DashAI framework using the llama.cpp backend. It enables efficient and flexible text generation with GGUF quantized models and supports private access using a Hugging Face API token.

Included Models

1. Gemma 3 1B It QAT

• Lightweight instruction-tuned model with 1.3B parameters
• Quantized and optimized for local inference (q4_0 format)
• Based on google/gemma-3-1b-it-qat-q4_0-gguf

2. Gemma 3 4B It QAT

• Instruction-tuned model with 4B parameters
• Balanced size and capability for local or cloud deployment
• Based on google/gemma-3-4b-it-qat-q4_0-gguf

Both models are instruction-tuned, designed for high-quality generation and compatibility with CPU or GPU inference using llama.cpp.

About Gemma

Gemma is a family of lightweight, state-of-the-art open models from Google, developed with the same technology as the Gemini models.
Key features of Gemma 3 models:

• Multimodal: support text and image input (in general; this plugin currently handles text-only generation)
• Large context window: up to 128K tokens
• Instruction-tuned variants available
• Multilingual: over 140 languages supported
• Open weights with access control via Hugging Face

Gemma is designed for deployment on laptops, desktops, and cloud infrastructure, making advanced AI more accessible.

Features

• Text generation via chat-style prompt completion
• GGUF format for optimized performance and memory usage
• Configurable generation parameters:
  • max_tokens: Output length
  • temperature: Output randomness
  • frequency_penalty: Controls repetition
  • context_window: Number of tokens per forward pass
  • device: "gpu" or "cpu"
• Automatic login to Hugging Face to access gated models

Model Parameters

Requirements

• DashAI
• llama-cpp-python
• Valid Hugging Face Access Token
• Model files from Hugging Face:
  • google/gemma-3-1b-it-qat-q4_0-gguf
  • google/gemma-3-4b-it-qat-q4_0-gguf

⚠️ Access Notice: You must accept the model terms on Hugging Face and use a valid Hugging Face token.
This repository is publicly accessible, but gated. You need to agree to share your contact information to access the model files.

Notes

This plugin uses the GGUF format, developed by the llama.cpp team for fast inference and low memory consumption.

The model is pretrained and instruction-tuned for inference and is not designed for fine-tuning.
Currently, this plugin supports only text generation (not image inputs).