README.md

metadata

title: Gemma 4 E2B QAT Mobile Demo
emoji: 💎
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.22.0
app_file: app.py
short_description: Multimodal chat demo of Gemma 4 E2B QAT Mobile
python_version: '3.12'
startup_duration_timeout: 30m

Gemma 4 E2B (QAT Mobile) — Multimodal Demo

A Gradio + ZeroGPU demo running unsloth/gemma-4-E2B-it-qat-mobile, the mobile-optimized (wNa8o8) quantization-aware-trained checkpoint of Google's Gemma 4 E2B model.

What it does

• Multimodal chat: text + image input, streaming text output.
• Optional thinking mode (the model reasons step-by-step before answering).
• Adjustable sampling (temperature / top-p / top-k / max tokens).

The model is a 2.3B-effective-parameter multimodal LLM (text, image, audio) quantized to ~2.5 GB via Unsloth's mobile-optimized wNa8o8 scheme, making it runnable on a single ZeroGPU.

Stack

• SDK: Gradio 6 on Hugging Face Spaces
• Hardware: ZeroGPU (zero-a10g) — free-tier friendly
• Model loading: transformers AutoModelForMultimodalLM + AutoProcessor

The first message after a cold start may take a few extra seconds while ZeroGPU streams the packed weights into VRAM.

Notes

• Image inputs are placed before the text, per the Gemma 4 best practices.
• Default sampling follows the official recommendation: temperature=1.0, top_p=0.95, top_k=64.