DigUp for Teachers

Download DigUp for Mac EmbeddingGemma 2 All roles

On-device flow Schematic: DigUp uses EmbeddingGemma 2 for Teachers local search

Original schematic — DigUp indexes local files with EmbeddingGemma 2 (llama.cpp).

Sourced snapshot (2026-10-15)

Fact	Value	Source
Model	EmbeddingGemma 2 · ~740M params · ~865 MB Q8 via llama.cpp	Google AI · DigUp README
Vector space	768-d shared multimodal space	Google AI · DigUp README
Mac / Win·Linux	0.6.1 · 0.7.0-beta.1	GitHub Releases
Stars / forks	~3,768 / ~254	GitHub API

Pain → DigUp workflow → tip

Pain	DigUp + EmbeddingGemma 2 workflow	Tip
Worksheet on fractions from last year	Index Teaching folders; semantic query	PDF/image hit
Recording of a demo experiment	Audio/video windows	Jump to explanation
Photo of student board work (local)	Image embeddings	Only folders you choose
Prep on a school laptop offline	On-device after model download	No DigUp account

Numbered checklist

Install DigUp; respect school privacy rules for student media.
Download EmbeddingGemma 2 (~865 MB) on campus Wi‑Fi.
Index curriculum folders; skip personal cloud junk.
Search learning objectives in plain language.
Use battery guide during long marking days.

Why EmbeddingGemma 2 matters here

Google’s EmbeddingGemma 2 (~740M, unified 768-d multimodal space) is what DigUp runs via llama.cpp (~865 MB Q8 package). One query can rank images, PDF pages, audio windows, video frames, and optional code — see the local multimodal guide and model page. digup.run is not Google-official.