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Running on Zero
A newer version of the Gradio SDK is available: 6.30.0
title: EmbeddingGemma 2 Search Lab
emoji: 馃攷
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 6.29.1
app_file: app.py
short_description: Explore task-aware embeddings and semantic search
python_version: '3.12'
startup_duration_timeout: 30m
EmbeddingGemma 2 Search Lab
Try Google's multilingual text embedding model in a small semantic-search workbench. Edit the document collection, enter a query, choose a retrieval task and embedding size, then compare the ranked results and cosine scores.
The app uses the model's asymmetric task instructions for queries and documents, and re-normalizes vectors after Matryoshka truncation. It loads only the text encoders to keep the demo lightweight. The underlying model also supports image, audio, and video embeddings.
Model
google/embeddinggemma-2 路 Apache 2.0 路 768-dimensional vectors 路 128/256/512/768 dimensions supported.
Run locally
pip install -r requirements.txt
python app.py
The model files are downloaded from Hugging Face on first startup. Access to the model may require accepting its terms on the model page.